digital yacht systems

AIS SYSTEMS

Internet on board, nmea interfaces, pc on board, portable navigation.

• AIS Transponders
• AIS Receivers
• VHF Splitters & Antennas
• AIS Accessories
• Antenna Mounts
• Multisensor
• NMEA to WiFi
• NMEA Interfaces
• NMEA 2000 Cables
• SeaTalk Interfaces
• USB Converters
• 4G/5G Internet Access
• Hi Power Long Range Wifi
• Cables & Accessories
• PC Accessories
• TV Antennas
• PC Software
• iPhone & iPad apps
• Android Apps

AIS SOLUTIONS

INSTRUMENTS SOLUTIONS

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NAVIGATION PC SOLUTIONS

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Digital Yacht is all about next generation navigation, communication and entertainment systems for your boat.

Our range of products.

Digital Yacht’s extensive range of AIS, internet onboard, sensors, NMEA, PC Onboard and softwares products provides solutions for every type of boat.

Our online articles

You will discover daily news-feed site about all Digital Yacht.

Our products videos

This platform contains lots of resources and tutorials about our products and softwares developed by Digital Yacht.

Who are we?

Digital Yacht is all about next generation navigation, communication and entertainment systems for your boat. Boating should be fun, safe and easy and our products integrate into existing and new boat networks to bring a powerful dimension to your on-board electronics.

We firmly believe that low cost consumer devices such as iPhones and tablets, PCs and MACs have a place on board and can help make legacy systems compete with the latest in dedicated marine electronic products at a fraction of the cost. We make internet access whilst afloat easy and affordable as well as bringing all your navigation data to your favourite consumer devices – not just for you but for crew and guests too.

Our navigation systems cover advanced GPS and compass technology as well as the most comprehensive range of AIS products in the marketplace. Plus our PC and software solutions bring simple yet powerful solutions to a variety of on board requirements from communication to navigation, entertainment to monitoring.

Our design team has 100’s years combined experience in marine electronic systems and we take pride in our quality heritage. Last year our products were sold in over 100 countries worldwide.

Manufacturing

We are proud that our production and development process takes place in Europe, as we are one of the only marine electronics companies which fully manufacture in Europe. A skilled and competent team of engineers work daily to improve our current products, as well as to develop new innovative products.

We have chosen to manufacture within Europe to provide our customers with the best products through a combination of high quality resources, skilled labour and innovative manufacturing technologies. Bristol is our production location and work with a loyal group of local contractors to create a lean manufacturing process. We use the United Kingdom as our centre of excellence to achieve our goal of creating much more durable and long-lasting products with the latest technical standards and highest reliability.

Our US sales and development office is located in Boston and our European facility is based in Rouen, France.

Our products are proudly designed in the UK, US and in France.

Dealers and distributors:

If you want to distribute our products, please contact us: [email protected]

All our products come with a comprehensive TWO year return to base warranty.

• Automatic Identification System (AIS)
• Navigation sensors
• Internet on board
• Portable Navigation
• NMEA to Wi-Fi Servers
• 4G Internet Access
• Accessories
• Entertainment
• MAC Software
• Connectors + Adapters
• PC Navigation
• Internet Access
• Product Manuals
• Product Firmware
• Technical Notes
• Utilities and tools
• Software and utilities
• USB drivers
• How to configure our AIS
• How to configure apps & software
• WLN10/WLN30
• Login / Register

Digital Yacht is all about next generation navigation,

Communication, and entertainment systems for your boat., discover our range of products.

Digital Yacht's extensive range of AIS, internet onboard, sensors, NMEA, PC Onboard and softwares products provides solutions for every type of boat.

Our online resources

you will discover daily news-feed site about all Digital Yacht

All videos about our products and softwares

This platform contains lots of resources and tutorials about our products and softwares develop by Digital Yacht

Who are we?

Digital yacht is all about next generation navigation, communication and entertainment systems for your boat. boating should be fun, safe and easy and our products integrate into existing and new boat networks to bring a powerful dimension to your on-board electronics. we firmly believe that low cost consumer devices such as iphones and tablets, pcs and macs have a place on board and can help make legacy systems compete with the latest in dedicated marine electronic products at a fraction of the cost. we make internet access whilst afloat easy and affordable as well as bringing all your navigation data to your favourite consumer devices – not just for you but for crew and guests too..

Our navigation systems cover advanced GPS and compass technology as well as the most comprehensive range of AIS products in the marketplace. Plus our PC and software solutions bring simple yet powerful solutions to a variety of on board requirements from communication to navigation, entertainment to monitoring. Our design team has 100’s years combined experience in marine electronic systems and we take pride in our quality heritage with manufacturing in the UK and global reach with offices in the US and China. Last year our products were sold in over 100 countries worldwide.

Manufacturing & technology, our products are designed and manufactured in the uk and us. we’re proud to be part of a hi-tech local manufacturing revolution. our technology encompasses specialist positioning and heading sensors, ais class a and b and receivers, nmea networking, wireless navigation and communication and on board networks and control systems. our uk r&d facility is located just outside bristol and we have electronic and mechanical assembly facilities in fareham and poole. our us sales and development office is located in boston and our china facility for software projects is based in shanghai., our range of products by digital yacht.

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Volvo Penta launches integrated hybrid-electric marine system

Monday, September 2nd, 2024

Written by: Marine Industry News

Volvo Penta has announced the release of its new helm-to-propeller hybrid-electric package, a fully integrated system that includes advanced drive modes and intelligent features. Production of the new hybrid-electric solutions will begin on a limited scale at the end of 2025 across Volvo Penta’s heavy-duty range.

The Volvo Penta hybrid-electric package is designed as a fully integrated system that operates “seamlessly from helm to propeller.” It combines electric and combustion power modes, which the firm says allows for smooth transitions and optimised performance.

The package offers near-silent cruising, battery-powered nights without the need for a generator, and features such as joystick driving and assisted docking in electric mode, enhancing ease of manoeuvring. The system is also designed to enable access to emission-free zones and environmentally sensitive areas.

“The hybrid-electric package represents our vision of technological innovation and efficient design, marking a significant step forward in marine technology,” said Johan Inden, president of the marine business at Volvo Penta.

The hybrid-electric package incorporates the Volvo Penta D13 IPS 900/1050/1200/1350 Hybrid, a 160 kW electric motor, and optimised batteries. The electric motor and diesel engine work in parallel on the same drive shaft, supporting pure electric, hybrid, and automatic power transition modes.

The cross-over mode enables one diesel engine to propel both drives, aimed at improving efficiency and reducing the frequency of engine maintenance. The system automatically selects between electric, combustion, or combined power based on the chosen drive mode.

The package utilises Volvo Penta’s Electronic Vessel Control (EVC) system to manage advanced features across different drive modes, including Joystick Driving, Joystick Docking, Low Speed, Dynamic Positioning System (DPS), and Assisted Docking. The Glass Cockpit system includes a hybrid-electric driver interface (HMI) with displays for drive modes and battery status. The EVC system supports engine monitoring, remote diagnostics, data sharing, and remote software updates, providing support through Volvo Penta’s global service network.

“Our hybrid-electric package integrates advanced technology with features adapted for electric use, such as DPS, Assisted Docking, and Joystick Driving. We aim to continue innovating to enhance the on-water experience,” says Inden.

The Volvo Penta hybrid-electric package is designed to provide a balanced experience at sea, with seamless transitions between electric motors and combustion engines that optimise acceleration and battery charging as needed. The Pure Electric mode allows for quiet, low-speed cruising, suitable for accessing environmentally protected areas. The system also enables off-grid mooring with battery-powered onboard systems, reducing the need for generator use.

The hybrid-electric system combines the range and speed capabilities of traditional engines with the near-silence and zero emissions of electric propulsion. This combination enhances onboard comfort, reduces noise, and improves responsiveness, while the large battery bank supports off-grid living.

Delivery of the D13 IPS hybrid-electric package will commence at the end of 2025.

In July, Volvo Penta expanded its range of remanufactured drivelines for marine customers . The new offer extends the remanufacturing range of products to include complete engines D13, D8, D4 and D6 and the complete Inboard Performance System (IPS) range.

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DISCOVER OUR RANGE OF PRODUCTS

AIS SYSTEMS

Digital Yacht’s extensive range of AIS products provides solutions for every type of boat.

INTERNET ON BOARD

Digital Yachts range of Internet products include Long Range Wi-Fi adaptors, 4G booster and wireless routers.

Digital Yacht’s GPS, Wind and Compass sensors offer Plug-And-Play compatibility with your PC and Navigation Systems.

NMEA INTERFACES

Digital Yacht’s Interfacing products provide smart and cost effective solutions for connecting dedicated marine electronics to the latest consumer devices such as smart phones, laptops and tablets.

PC ON BOARD

A Digital Yacht PC not only brings email and web access but also Electronic Charting, Navigation and entertainment onto your boat.

PORTABLE NAVIGATION

Digital Yacht’s innovative navigational software and application solutions for PCs, Tablets and Smartphones are powerful and easy to use..

ABOUT DIGITAL YACHT

Boating should be fun, safe and easy and our products integrate into existing and new boat networks to bring a powerful dimension to your on-board electronics.   Our design team has 100’s years combined experience in marine electronic systems and we take pride in our quality heritage with manufacturing in the UK and global reach with offices in the US and France. Last year our products were sold in over 100 countries worldwide.

OUR SOLUTIONS

AIS SOLUTIONS

INSTRUMENTS SOLUTIONS

INTERNET SOLUTIONS

NAVIGATION PC SOLUTIONS

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EU Entry/Exit System

Information and advice on the new EU Entry/Exit System

From autumn 2024, the EU will be introducing a new digital border system to strengthen the security of its external Schengen border. 

The new registration process – called the Entry/Exit System, or EES for short - is expected to be introduced in November, however the EU has yet to confirm a specific date for its introduction.  

It will apply to those travelling to the Schengen area which encompasses all EU countries, except from Cyprus and Ireland. Additionally, the non-EU States Iceland, Norway, Switzerland and Liechtenstein are also part of the Schengen area. ​ This will require most citizens of countries outside the EU to create a digital record and register their biometric details, such as providing fingerprints and having their photo taken, when they enter the Schengen area. This should only take a few minutes for each person to do.  ​ ​ British travellers will need to do this on their first visit to the EU after EES is introduced.​ Their record will be checked on point of entry into the Schengen area verifying either their fingerprint or photograph. 

At some ports in the South of England (Dover, Eurotunnel and St Pancras - where the French Border Force operate immigration checks in the UK), EES will be carried out before departure. There may be increased wait times while EES registration is completed before passengers leave the UK. ​ If British travellers decide to visit a country in the Schengen area again within a three-year period of creating their digital record, they will only need to provide either their fingerprint or photograph at the border on entry and exit.

EES will bolster border security for both the EU and their neighbouring countries. 

More information on EES can be found on the EU’s official Travel Europe website .

Why is the EU introducing EES?

EES is designed to improve border security, including tackling illegal migration in the Schengen Area by keeping a new digital record of people that enter.  ​

It will also replace the current system of manually stamping passports every time someone enters a country in the EU, with more automated border control checks to help the EU ensure that people do not overstay.​

EES is part of wider work the EU is doing to strengthen their border security – in 2025, the EU will introduce the new European Travel Information and Authorisation System (ETIAS).  ​

ETIAS will mean that those travelling to the Schengen area need to submit information about themselves and their travel plans, and pay a fee of 7 Euros, to apply for authorisation to travel before they leave for the Schengen area.

The EU has already set out more information on ETIAS, including what information will be required from each nationality. This can be found on the EU’s official Travel Europe website .

The impact on journeys to the Schengen Area 

When EES is introduced, travellers will be required to register at the Schengen border. They’ll do this at the port or airport on arrival, where they can submit their fingerprints and have their photo taken at dedicated booths. 

While the checks will only take a few minutes for each person to do, it may lead to longer queue times for people travelling to countries in the Schengen area.  ​

Travellers will only need to submit their biometric information at the border, and when EES is first introduced, they will not be required to provide any further information before they travel.​

At some ports in the South of England (Dover, Eurotunnel and St Pancras - where the French operate juxtaposed immigration checks in the UK), there may be increased wait times while EES registration is completed before passengers leave the UK. ​ ​ Passengers travelling through one of these ports should check with their travel operator before they leave to travel, to understand when to arrive at the port and any potential impacts to their journey.​

If travellers are flying to a country in the Schengen area, they may experience longer queue times when they arrive while EES registration is completed.

The Government is taking action to minimise the impact of EES

The EES is an EU initiative, and the UK Government has been reviewing the preparations made to date.

The UK Government has been working closely with the European Commission, member states, local authorities and the travel industry, taking a multi-agency approach to ensure Ports are prepared for the introduction of EES. 

The Government has been supporting ports and carriers to make sure they have the right technology and processes in place so EES registration can take place as smoothly as possible. 

Recently, the UK Government provided Eurostar, Eurotunnel and Port of Dover £3.5m of funding each, which they are spending on more kiosks and infrastructure.

Eurostar will have almost 50 kiosks for people to carry out the checks, and these will be spread across three locations at the station. It expects EES registration to be quick and easy. ​

Eurotunnel will have over 100 kiosks and estimate EES checks will add just over 5 minutes to journey times.​

Port of Dover will have 24 kiosks for coach passengers and will register passengers in cars using agents and tablets to make the process as straightforward as possible.

Where can I find out more information about EES?  

You can visit the EU’s official Travel Europe website .

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• Access coarse (e.g., Cell-ID, Wi-Fi) location
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Digital Yacht at Newport International Boat Show 2024

ePropulsion electric engine monitoring on EngineLINK

Digital Yacht at Sydney Boat Show 2024

Webinar on 4G and 5G Internet routers for your boat.

Digital Yacht launches LANLink NMEA to Ethernet Gateway

Digital Yacht’s  LANLink is a NMEA to ethernet gateway which enables the boat’s NMEA data to integrate onto the router network.

More and more boats now have a wireless router fitted or utilise devices like our 4G Connect for internet connectivity. Installing LANLink via a simple ethernet patch cable to the router allows connected devices and apps to take advantage of the NMEA data.

LANLink is available in two versions suitable for NMEA 0183 and NMEA 2000 respectively. It features an easy to use web interface allowing any device with a browser to configure NMEA baud rates and IP/Port information.

It can support multiple TCP/IP connections and is bi-directional. Once connected to the onboard network via a simple CAT 5/6 patch cable, you can setup apps like TZ iBoat, iNavX, NavLink, iSailor, Imray, Weather 4D etc by simply entering the IP address and port for streaming NMEA data.

LanLINK   is shipping now. A dealer and partner introduction pack is available from the download link below or from  HERE

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Happy christmas from digital yacht, digital update january 2021 now available.

• Digital Yacht

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Digital Yacht is all about next generation navigation, communication and entertainment systems for your boat.

Our range of products.

Digital Yacht’s extensive range of AIS, internet onboard, sensors, NMEA, PC Onboard and softwares products provides solutions for every type of boat.

Our online articles

You will discover daily news-feed site about all Digital Yacht.

Our products videos

This platform contains lots of resources and tutorials about our products and softwares developed by Digital Yacht.

Who are we?

Digital Yacht is all about next generation navigation, communication and entertainment systems for your boat. Boating should be fun, safe and easy and our products integrate into existing and new boat networks to bring a powerful dimension to your on-board electronics.

We firmly believe that low cost consumer devices such as iPhones and tablets, PCs and MACs have a place on board and can help make legacy systems compete with the latest in dedicated marine electronic products at a fraction of the cost. We make internet access whilst afloat easy and affordable as well as bringing all your navigation data to your favourite consumer devices – not just for you but for crew and guests too.

Our navigation systems cover advanced GPS and compass technology as well as the most comprehensive range of AIS products in the marketplace. Plus our PC and software solutions bring simple yet powerful solutions to a variety of on board requirements from communication to navigation, entertainment to monitoring.

Our design team has 100’s years combined experience in marine electronic systems and we take pride in our quality heritage. Last year our products were sold in over 100 countries worldwide.

Manufacturing

We are proud that our production and development process takes place in Europe, as we are one of the only marine electronics companies which fully manufacture in Europe. A skilled and competent team of engineers work daily to improve our current products, as well as to develop new innovative products.

We have chosen to manufacture within Europe to provide our customers with the best products through a combination of high quality resources, skilled labour and innovative manufacturing technologies. Bristol is our production location and work with a loyal group of local contractors to create a lean manufacturing process. We use the United Kingdom as our centre of excellence to achieve our goal of creating much more durable and long-lasting products with the latest technical standards and highest reliability.

Our US sales and development office is located in Boston and our European facility is based in Rouen, France.

Our products are proudly designed in the UK, US and in France.

Dealers and distributors:

If you want to distribute our products, please contact us: [email protected]

All our products come with a comprehensive TWO year return to base warranty.

• Automatic Identification System (AIS)
• Navigation sensors
• Internet on board
• Portable Navigation
• AIS Transponders
• AIS Receivers
• VHF Splitters & Antennas
• AIS Accessories
• Multisensor
• NMEA Interfaces
• NMEA to Wi-Fi Servers
• NMEA 2000 Cables
• SeaTalk Interfaces
• USB Converters
• 4G/5G Internet Access
• Hi Power Long Range Wifi
• Accessories
• PC Accessories
• TV Antennas
• PC Software
• Apple & Android apps
• Antenna Mounts
• Connectors + Adapters
• Internet Access
• PC Navigation
• Product Manuals
• Product Firmware
• Technical Notes
• Utilities and tools
• Software and utilities
• USB drivers
• Get Support
• Product Registration
• Product Return Form
• How to configure our AIS
• How to configure our 4G products
• How to create an NMEA 2000 network
• How to configure apps & software
• Technical FAQs
• Products with NMEA 2000 interface
• WLN10/WLN30
• Login / Register

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PORTABLE NAVIGATION

What is portable navigation.

At Digital Yacht we define Portable Navigation as being able to use a laptop, tablet, smartphone for navigation and mapping. With the rise of technology, portable navigation is becoming more and more common.

Navigation applications and software are more and more popular and numerous for Android or Apple products and now most of them support NMEA data allowing your tablet, smartphone, laptop to become a complete and trusted navigation system.

By connecting an  NMEA to WiFi adaptor  or an  NMEA to USB adaptor , your navigation software or iOS/Android app will be connected to your navigation system (chart plotter, instruments, autopilot, AIS, etc.). Then, your software or navigation app will display in real time AIS targets, GPS, Wind and all navigation information.

Digital Yacht   has also developed innovative, easy to use and powerful apps and navigation software for smartphones, tablets and PCs. However, our NMEA to WiFi adaptors and NMEA to USB connectors are fully compatible with all the popular navigation software and apps

We have developed a list of the best apps for iOS (iPhone/iPad) and Android which you can discover here:

Benefits of iPad & Tablet navigation

There are numerous benefits of using an iPad or tablet for navigation. Obviously, the financial aspect is the most important for portable navigation, where a simple system allows you to get all navigation data on your mobile devices. With most people already owning a tablet or smartphone, the user only needs to purchase the product needed to transmit the data to these devices.

Tablet navigation also gives the user the ability to greatly improve their electronic system and utilise a navigation system with unlimited functions. If a chart plotter is already owned, customers can connect their existing plotter system to a product that will broadcast NMEA data wirelessly. This works with all major brands including Raymarine, Navico, Furuno, Garmin, etc.

This means that if the customer already has a tablet or smartphone they will receive the data and be able to use comprehensive and powerful applications or navigation software. For example, the customer will be able to broadcast AIS data on a tablet that they can use cooperatively with their plotter and therefore he will be able to navigate and track a route on the existing plotter and at the same time look at the surrounding AIS targets on the tablet.

In addition to navigation and cartography, having an iPad, Tablet or Smartphone on board allows you to connect to the internet (if you have access) and therefore check your emails, surf the internet, Youtube, Facebook, etc.

Moreover, the portable navigation is a backup solution in case of problems with your main chart plotter. Also if your chart plotter has a small display, portable navigation can be a perfect solution for you. For a minimal cost, you will get all your data on a much larger screen. Chart plotters are limited to navigation, whilst tablets can also display weather data and receive navigation data from the internet too.

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NMEA to WiFi

Our NMEA to WiFi servers to connect your tablet/iPad to your navigation system.

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• Automatic Identification System (AIS)
• PC on Board
• Portable Navigation
• AIS Receivers
• AIS Transponders
• VHF Splitters & Antennas
• AIS Beacons
• AIS Accessories
• Multisensor
• NMEA to WiFi Servers
• NMEA Interfaces
• NMEA 2000 Cables
• SeaTalk Interfaces
• USB Interfaces
• 4G/5G Internet Access
• Hi Power Long Range Wifi
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1 Introduction

2 preliminary, 3 guidance and controller design, 4 experiments, results, and discussion, 5 conclusions and future research, funding data, data availability statement, adaptive dynamic model-based path following controller design for an unmanned surface vessel.

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Zhu, M., Wen, Y., Tao, W., Xiao, C., and Sun, W. (August 29, 2024). "Adaptive Dynamic Model-Based Path Following Controller Design for an Unmanned Surface Vessel." ASME. J. Dyn. Sys., Meas., Control . January 2025; 147(1): 011004. https://doi.org/10.1115/1.4065802

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The effective design of a path-following controller for unmanned surface vessels (USVs) under uncertain influences induced by various factors such as environmental disturbances is a challenging task. In this study, we propose to fulfill this task through taking benefits from an online parameter identification technique, the discrete-time sliding mode control (DSMC) method, and the improved line of sight (LOS) algorithm. The Particle Swarm Optimization algorithm (PSO) was adopted to provide initial settings for the straightforward online identification method, i.e., the Forgetting Factor Recursive Least Square method (FFRLS). In order to handle the time-varying sideslip angle of a ship that exists in reality due to environmental disturbances, a multimodel course control scheme is proposed to improve the control performance. For this control scheme, a flexible selection mechanism in between a heading angle or a course angle tracking controller based on the DSMC method is designed. A solution to fixing the tracking deviation problem of the LOS guidance law is investigated for which the gradient descent method is introduced. A series of experiments are carried out at sea with a USV called Orca to verify and validate the proposed hybrid path following approach. The results showed that tracking errors mainly induced by environmental disturbances existed but the maximum magnitude among them was small enough and remained within the acceptable range, especially from the marine engineering point of view. These results, to a high degree, validated the robustness and precision of the proposed controller.

Unmanned surface vessels (USVs) are vital to numerous applications such as transportation, environmental monitoring, exploration, and rescue [ 1 – 6 ].

The study of USVs has been developed as an interdisciplinary field involving, e.g., advanced control theory, mechanical, electronic. Effective motion control is of significant importance to ensuring navigation safety for USVs. The key components for the motion control of USVs are guidance, navigation, and control (GNC) which play a critical role to the development of USV's intelligence and autonomy [ 7 – 12 ]. In particular, the utilization of high-performance guidance and control methods is in high demand to increase the deployments and applications of USVs [ 13 – 15 ].

As one critical aspect of the motion control system, the path following issue of USVs is investigated in-depth in this study. Given a typical motion control scenario, the path following makes a vessel follow a predefined geometric path without any time constraints [ 16 – 19 ]. The holistic task was completed mainly depending on three subsystems which are guidance subsystem, dynamic model regarded as the control model, and control subsystem [ 13 , 18 ].

Generally, it is hard to describe and capture USV's motions with high reality due to some complicated characteristics such as hydrodynamic interactions, underactuated propulsion systems [ 13 , 20 ]. The above fact means that it is challenging to develop a path-following controller with an accurate dynamic model. Therefore, many researches are devoted to the establishment of simplified dynamic models of USV systems among which some have been applied in practical engineering [ 21 – 24 ]. From the study in Refs. [ 21 ] and [ 25 ] where a simplified forward speed model for capturing surge motion in combination with a Nomoto model with sideslip angle in describing steering motion was employed in the development of USV controller, we can see that the applied control model matches well the requirement. Therefore, such control model will be employed in this study. After the model is determined, the parameters involved in the model should be estimated through suitable method, which is able to be de-alt with by the system identification technique.

Typical methods used in system identification procedures can be classified into offline method and online method. Among offline identification methods, least squares (LS) method [ 26 , 27 ] is one. However, intelligent identification methods sometimes suffer from local optimum, cannot always guarantee global optimal results of the most common method to estimate parameters and it is sensitive to outliers. Genetic algorithm (GA) [ 28 ] and Neural Network (NN) based method [ 29 ] are advanced system identification techniques proposed based on intelligent identification methods [ 30 ]. In online identification techniques, Extended Kalman Filter (EKF) is one widely-used approach in solving vessel dynamic model identification problem [ 31 , 32 ], but it seriously depends on the initialization of covariance matrix and the time complexity would increase along with the number of the parameters required to be estimated. Comparatively, the FFRLS as a straightforward online identification method is developed to tackle the ill-conditioned problem of LS but inherits the merits of LS. The FFRLS is suitable for online parameter identification of the control model at high frequencies owing to its lower computational complexity and faster calculation speed [ 23 ].

Besides, the phenomenon of data saturation during continuous online recursive operation can be mitigated in the FFRLS. Consequently, the relevant data sampled can maintain the ability to correct the estimated value of unknown items in the system model. In this study, the FFRLS is employed as a parameter identifier for the determined control model. To improve the performance of FFRLS on defending time-varying disturbances, an optimizer, i.e., Particle Swarm Optimization algorithm (PSO) is selected to provide initial settings for the FFRLS. The PSO has the characteristics of fewer requirements for initial values and strong anti-interference ability, which is widely used as optimizer [ 33 , 34 ].

Several guidance principles have been developed. The line of sight (LOS) algorithm [ 35 ] and vector field (VF) algorithm [ 36 , 37 ] are two famous methods. Comparatively, LOS is more easy-understanding and flexible [ 38 ].

According to the vessel operation experiences of crews and captains, it is relatively more effective to control course or heading rather than speed of vessels. In order to solve the course angle control problem for USVs, several typical approaches can be applied. In some experiments, the conventional PID control method has been applied [ 39 ]. Nonlinear model predictive control has been applied to control the fully actuated autonomous surface crafts under constant ocean currents [ 40 , 41 ]. Refs. [ 21 ] and [ 42 ] employed feedback linearization and backstepping methods for the nonlinear control of a USV. As a nonlinear control method, sliding mode control [ 43 , 44 ] has attractive characteristics such as simple structure, strong anti-interference ability, insensitivity to parameter changes, and good control performance for nonlinear systems [ 45 ]. However, the conventional sliding mode control system is not so applicable to situations with the limitation of the actual control system in sampling the frequency and actuator movement speed. To remedy this deficiency, the discrete sliding mode control is proposed, which can be directly used in computer control systems while retaining the advantages of the sliding mode control [ 46 – 49 ]. In discrete sliding mode control, how to reduce system chattering is also the main problem faced by the popularization of sliding mode control methods. Since available position data (such as GPS data) are easily affected by various uncertainties from the environment, it is difficult to obtain consistent position data of USVs. Therefore, this study proposes a controller that follows the reference course angle, which comprises the sideslip angle and yaw angle corresponding to the waypoint sequence given in advance. The slipping motion generated by sway disturbances could be avoided by the designed course angle controller.

Path following is one of the most fundamental functions of a USV. In addition to collision avoidance, platooning sailing, and cooperative control, USV may do more sophisticated tasks based on its ability to follow a path [ 50 ].

To address the path-following problem, previous research has considered various approaches, including model-based control, guidance algorithms, and hybrid control methods. Some common model-based control methods include proportional-derivative (PD) control [ 51 ], linear quadratic regulation (LQR) [ 52 ], and model predictive control (MPC) [ 53 ]. Guidance algorithms, such as the line-of-sight (LOS) method [ 54 ], provide the desired path for the vessel to follow. Hybrid control approaches, such as the combination of PD control and LOS guidance, have also been proposed to take advantage of the strengths of different methods.

In past research, intelligent adaptive control and guidance methods are employed for the path following controller design, such as Ref. [ 23 ]. However, the actual navigation environment of USV is complex and changeable. It is difficult to follow changing paths based on the traditional method (such as LOS, VF guidance laws) in traditional geometric solution problems.

Current USV path following challenges include optimization of USV dynamics, motion model accuracy, and controller settings [ 55 , 56 ]. It's important to note that the selection of a path-following approach depends on the specific requirements of the application and the characteristics of the vessel. As an unsupervised learning method, an improved LOS guidance algorithm-based path following control method is designed, which has natural advantages over traditional control methods in the USV path following control.

From the relevant literature, the consideration of sideslip angle in designing path following is an effective idea. The uncertainties existing in sideslip angles are investigated in this path following controller study which is a novel inspiration for improving robustness of the controller.

Many control Papers have been studied to achieve better control performance, but few methods could deal well with the integrated challenges consisting of the USV's nonlinearities, modeling uncertainties, and external disturbance. Therefore, good path following performance is still challenging to develop for real USV's control.

In summary, the main contribution of this paper is the development of an adaptive path-following controller for underactuated USVs by incorporating the improved LOS guidance algorithm and online course controller defined as DSMC.

The modeling uncertainties are related with the motion state and dynamic parameters of the USV. To approximate and compensate uncertainties, the control model adopted with uncertain sideslip angle induced by complex environment disturbances is identified using effective online identification method.

A single model is not enough to describe the motion characteristics of the USV in different environments, thus affecting the path-following effect. Therefore, using the corresponding model for the path tracking controller design can be considered for different situations ((1) straight path and (2) cure path or turning). A multimodel course control scheme is investigated to fix the problem about side angle change existing in the operation of a USV.

Because the USV should have the ability to track the curved path due to the mission requirements, and the USV has a sideslip angle problem during the steering process. Based on the analysis of the deviation calculation method of the LOS guidance law, the geometric problem is transformed into an optimization problem, and the gradient descent method is introduced to calculate the deviation online to obtain the LOS curve guidance law. Finally, an improved LOS guidance algorithm-based path following control method is designed.

In order to design an effective path-following controller for underactuated USVs with time-varying sideslip angle, we focus on simultaneously benefiting from the discrete-time sliding mode control (DSMC) method, online parameter identification technique, and improved line of sight (LOS) algorithm to design a suitable controller. Accordingly, heading angle and course angle adaptive discrete sliding mode controllers are designed.

The remainder of this paper is organized as follows: Section 2 describes the mathematical dynamic model of USVs and the discrete sliding mode control method. The research object is concretely introduced in Sec. 3 where the control model and the discrete sliding model control method are also presented. Section 4 presents four types of case studies to evaluate the proposed method. Finally, conclusions and directions for future research are given in Sec. 5 .

The design and construction of the control system of the Orca USV platform are presented in Sec. 2 . Subsequently, the ship response model with a sideslip model is described, followed by details regarding the discrete-time sliding mode control algorithm.

2.1 Ship Response Model.

where β = a tan 2 ( v , u ) ⁠ , and then the steering motions of USV were setup as shown in Fig. 1 .

Horizontal plane coordinates

where a β = − 1 T β ⁠ , b β = − K β T β ⁠ , a r = − 1 T ⁠ , and b r = − K T ⁠ . k and t are parameters of vessel's Nomoto model (KT Equation), δ r is rudder angle of vessel, r is angular velocity of vessel, β is sideslip angle of vessel, ψ is heading angle of vessel, k β and t is parameters of vessel's sideslip angle model.

where b u = K m m − X u ˙ ⁠ , δ T ∈ ( 0 , 1 ) is the opening signal of throttle.

2.2 Reaching Law-Based Discrete-Time Sliding Mode Control.

where x ( k ) is an n-vector, u i ( k ) is a scalar, A and B are appropriate matrix, and C = [ c 1 , c 2 , … , c n ] , c n = 1.0 ⁠ .

Exponent reaching law is a controller design method in the DSMC theory. Functionally, it can not only analyze the motion state of the system on the sliding mode surface, but also effectively design the dynamic process of the approaching section system, and finally ensure the good quality of the control system during the entire control process.

The control process of the system is shown in Fig. 2 . First, the reference trajectory is set, and the guidance algorithm calculates the reference heading command given to the control system according to the real-time motion state of the ship. Then, the control system calculates the control command based on the ship's current state and reference angle. In parameter identification of the control loop, the initial values of the relevant controller's parameters are calculated by the PSO algorithm using historical data. Next, the FFRLS algorithm is used for online identification to update the relevant controller's parameters in real-time. Finally, the USV executes the control command, collects the relevant data through the sensor, and transmits it to the guidance and control system.

The system control process

3.1 Parameter Identification.

The identification methods including the PSO and FFRLS are proposed in this section to estimate the parameters involved in the response model established in Sec. 2.1 . Considering that some parameters impacting the performance of FFRLS are required the initialization procedure, the PSO is applied first to fulfill such requirements. Firstly, the initial parameters of the response model are obtained using the PSO optimization algorithm based on historical data. Then, the FFRLS is employed as the online identifier responsible for the real-time identification of the response model parameters.

3.1.1 Particle Swarm Optimization.

PSO is a group-based optimization method [ 60 , 61 ]. This algorithm is inspired by the intelligent behavior of social birds in nature when searching for food. Each particle adjusts its speed and position according to the global optimal solution and starts the next iteration.

where w ini is the initial inertia factor, w end is the inertia factor when iterating to the maximum algebra, and G k is the maximum number of iterations.

where A pso = [ A i j ] = [ a u 0 0 0 0 a β 0 b β 0 0 0 1 0 0 0 a r ] ⁠ , B pso = B k l = [ b u 0 0 0 0 0 0 b r ] . x = [ u , β , ψ , r ] , δ = [ δ T , δ r ] are input quantity for throttle and rudder angle.

where Δ t is the sampling time.

3.1.2 Forgetting Factor Recursive Least Square.

Combining the discretized model shown in Eqs. (19) and the motion state data obtained in real-time during the actual navigation of the USV, we can realize the online identification of the response model by using (18) .

3.2 Multimodel Course Control Scheme Based on Discrete-Time Sliding Mode Control.

For the control of USV, the Nomoto model is usually used for controller design. However, the Nomoto model assumes that the ship's direction of motion is consistent with the ship's heading direction, for the USV with vector propulsion, the direction of motion and the ship's heading direction during the steering movement usually have a certain sideslip angle. According to the analysis in Sec. 3.1 , the Orca USV has the sideslip angle during the steering movement, and the sideslip angle changes along with the speed.

From the perspective of practical application, the heading angle information of the USV is relatively easy to acquire with high accuracy via available sensors such as compass during navigation period. Therefore, an adaptive selection mechanism is put forward to make the control system more flexible and effective. When the sideslip angle was small enough with ignorable effects, the first-order linear Nomoto model would be used in process of controller design. Otherwise, the Nomoto model with sideslip angle would be utilized.

Generally speaking, when the USV is tracking a straight path, the self-adaptive discrete sliding mode heading angle controller is used. when the ship is tracking a curve or turning, the self-adaptive discrete sliding mode course controller is selected to solve the sideslip angle problem in the actual sailing of the ship. Correspondingly, it is named a multimodel course control scheme.

3.2.1 Self-Adaptive Discrete Sliding Mode Heading Angle Controller Based on Exponential Reaching Law.

where G ( t s ) = e A t s ⁠ , H ( t s ) = ( ∫ 0 t s e A t d t ) B are state transition matrix of the system.

where A = [ 1   T ( 1 − e − 1 T t s ) 0   e − 1 T t s ] ,   B = [ K ( t s + T e − 1 T t s − T ) K ( 1 − e − 1 T t s ) ] ⁠ .

According to Ref. [ 46 ], let ε = | s ( k ) | 2 ⁠ . If the sampling time t s is satisfied t s < 4 1 + 2 q ⁠ , the Eq. (32) holds.

The maneuverability index of USV can be obtained by the offline identification method to obtain the initial value to determine the element initial values of the parameter matrix A and B, and in the experiment, the maneuverability index can be obtained online by FFRLS.

3.2.2 Self-Adaptive Discrete Sliding Mode Course Angle Controller Based on Exponential Reaching Law.

where x 2 = [ β ψ r ] , A = [ 0 1 0 0 0 1 0 − 1 T T β − T + T β T T β ] ⁠ , B = [ 0 , 0 , K K β T T β ] T , u = δ r .

where R is the course angle instruction.

3.3 Stability Analysis

3.3.1 system stability analysis..

Theorem 1. Assume underactuated USV closed-loop system satisfying Eqs. (20) and (24) , under the adaptive slide mode control law's control. For any initial condition, by adjusting the design parameters, the tracking error gradually converges to the area where the zero value is small, and the system is guaranteed to be globally stable .

Therefore, the control system involved is stable.

3.3.2 Analysis of System With Disturbances.

The outstanding advantage of sliding mode variable structure control is that it can realize that the sliding mode is completely independent of the disturbance and parameter identification of the system. This property is called the invariance of the sliding mode.

It can be seen that the system is completely immune to parameter change and external interference, and this characteristic of sliding mode variable structure control is called invariance.

3.4 Line of Sight Guidance.

LOS guidance for MASS

When using the conventional LOS guidance law for linear path tracking, the geometric algorithm is usually used to mensurate the closest point from USV to reference path. But for a complex path, the closest point cannot be determined in this way.

Parametric path LOS guidance law

where Δ θ LOS is equivalent to the forward-looking distance in the linear LOS guidance law.

3.5 Path Following Controller Design.

This section adopts an indirect path following control scheme. On the basis of the self-adaptive discrete sliding mode heading angle controller and self-adaptive discrete sliding mode course angle controller in Sec. 2.2 , the LOS guidance law in Sec. 3.4 is used to design the path following controller as shown in Fig. 5 .

The structure of the path following control system

Its specific structure is shown in Fig. 5 . Firstly, the guidance out-loop calculates and generates the heading command through the guidance algorithm based on the feedback position information. Then, the control inner-loop uses the self-adaptive discrete sliding mode control law designed in Sec. 2.2 to calculate and obtain the current USV's current rudder angle command. Finally, the rudder angle control node calculates the control amount based on the expected rudder angle and the current rudder angle feedback value and sends it to the actuator to drive the outboard motor to rotate, thereby driving the USV to follow the course command.

When the USV enters the trajectory error zone in straight-line path, the main task is the course-keeping, and the sideslip angle is usually small. Therefore, the heading angle control of the inner control loop should have better control quality. When the USV is tracking curve path, the main task is to track the course. The sideslip angle is larger at this moment because the expected course changes at all times, so the control inner-loop should adopt the course angle control.

In this section, experiments are carried out to illustrate the potential of the proposed approach. We are considering building an autonomous ship platform for the experimental test platform first. Then the unknown parameters in the ship operation response model are identified. Finally, the heading and course angles control experiment and path tracking experiments are carried out in the natural sea area to illustrate the feasibility of the proposed control method. The results are compared with the existing techniques to prove that the proposed method can effectively improve the control accuracy compared with the current control methods. Specifically, we will conduct heading and course angles control experiments and Path-following experiments.

4.1.1 Unmanned Surface Vessel.

An unmanned surface vessel was used in the experiments, Orca. Orca is a USV. In order to verify the effectiveness and universality of the control method in this article, we built an autonomous ship experimental platform. We designed a controller to verify the path-following control method in the actual environment to ensure that the tracking error of the path-following controller is less than the length of the ship after converges.

Considering compatibility and scalability of common platforms, a 7.6 m planning craft (Fig. 6 ) and a Honda BF15D 115 HP outboard engine motor are selected according to the stability and simplicity of the steering mechanism. To perform the desired operation, some shipborne perception and global monitoring sensors such as compass, global positioning system (GPS), lidar, radar, camera, and inertial measurement unit (IMU) are equipped on Orca.

The experimental platform of the Orca

The control system of Orcais mainly made up of a host computer, a control computer, a signal acquisition electronic control unit (ECU), and a drive ECU. The actuator is mainly composed of a 115 HP engine, throttle control device, and steering system. The throttle control device is a KE4+ control system comprising a control handle, a controller, and an actuator. The steering system is composed of a steering wheel, an oil pump, an oil cylinder, an electric navigation pump, and a hydraulic pipeline, with both manual steering and automatic control capabilities.

The communication and control system of the OrcaASV is designed as a distributed communication system based on the universal serial bus(USB) and network communication. Figure 7 shows its overall structure.

The overall structure of the ASV hardware system

4.1.2 Experimental Area.

A port of the Nanhai in the south of Weihai City is selected as the experimental area (Fig. 8 ). There were three kinds of experiments set in this sea area, including identification, heading control, and path-following control.

Experiments area

The proposed path following controller is verified by several sets of experiments on the Orca USV. The control system of Orca was setup, as described in Sec. 4.1.1 . In order to estimate its own motion state and perceive the surrounding environments of Orca, an IMU sensor and GPS antenna/receiver were equipped onboard. Finally, the control system needs to calculate the control input command of USV, and also needs to ensure that all sensors collect and process the data sets that are certainly needed.

4.2 Identification Results.

The Froude coefficient Fr is an important parameter for ship model experiments. Its value can be calculated using the formula F r = U L g and can be used to distinguish the motion state of ships, where U means USV's velocity, L means USV's waterline length, and g is the acceleration due to gravity. According to Refs. [ 21 ] and [ 64 ], When the ship is in the displacement mode, the weight of the ship is almost completely supported by the buoyancy hydrostatic forces, and the Froude coefficient is less than 0.5. When the ship is in the semidisplacement mode, the weight of the ship is completely supported by both the hydrostatic and hydrodynamic forces, and the Froude coefficient is between 0.5 and 1.0. When the ship is in the planning mode, the hydrodynamic forces dominate, and the Froude coefficient is greater than approximately 1.0–1.2.

The Orca USV is designed as a planning vessel, planning is the mode of operation for a waterborne craft in which its weight is predominantly supported by hydrodynamic lift, rather than hydrostatic lift. A planning vessel is a vessel that can achieve the planning state. However, each of the three modes can routinely be operated. Therefore, when designing a USV experiment, the influences of the three different modes on the maneuvering response model must be considered. Table 1 lists the critical speed values of the Orca USV under three different sailing conditions.

Three modes of Orca USV

A series of experiments of a field USV were carried out to investigate the exactness of the established steering model. Multiple sets of cycles and Z-shaped experiments at different speeds were designed to determine the values of K and T, respectively.

The PSO algorithm and offline data were used to identify the K value; Table 2 lists the change in the rudder index K of the Orca USV with the rudder angle at different speeds. Considering the safety of the experiment, the high-speed rudder angle rotation experiment was not conducted.

The change of the rudder index K of Orca MASS with the rudder angle

As listed in Table 2 , because of the difference in the velocity and rudder angle of the USV, the rudder index K varies in a certain range, consistent with the actual operating principle.

To obtain experimental data under different maneuvering conditions, the rudder angles were set to 10 ∘ / 10 ∘ ⁠ , 15 ∘ / 15 ∘ ⁠ , 20 ∘ / 20 ∘ and 10 ∘ / 40 ∘ for small rudder angle and large-angle Z-shaped steering experiments.

The PSO algorithm and offline data were used to identify the T value; Table 3 lists the change in the corresponding index T value at different velocities.

The changes of the T

Considering the safety of the experiment, the high-speed large rudder angle Z-shaped experiment was not conducted.

Figures 9(a) – 9(d) and Table 4 show the semidisplacement mode (velocity is approximately 4.0 m/s); the average deviations of the actual angular velocity of the USV and the result of the mathematical model are calculated for comparative analysis.

Experimental results of system identification test 1: ( a ) comparison of estimated data and real data at 10°/10°, ( b ) comparison of estimated data and real data at 15°/15°, ( c ) comparison of estimated data and real data at 20°/20°, and ( d ) comparison of estimated data and real data at 10°/40°

The average deviation between the predicted value of angular velocity and the measurements

Experimental results of system identification test 2: ( a ) comparison of estimated data and real data at a speed of 3.0 m/s, ( b ) comparison of estimated data and real data at a speed of 4.5 m/s, and ( c ) comparison of estimated data and real data at a speed of 7.1 m/s

The average deviation between the predicted value of the sideslip angle and the measurements

As shown in Fig. 10 , the first-order inertia can help characterize the relationship between the sideslip angle and the angular velocity of the Orca USV. Table 6 lists the values of K β ⁠ , T β at three different speeds.

The value of K β , T β at three speeds

4.3 Results of Heading and Course Angles Control.

During the actual operation of the Orca USV, its maneuverability index will vary with the ship velocity, fuel consumption, and external interference. To check the control effect of the designed heading angle controller, a field experiment on heading control at speeds of approximately 3.0 m/s (displacement mode) and 4.2 m/s (semidisplacement mode) was designed. On the day of the experiment, the wind speed was around 2.5 m/s, and the USV was strongly affected by winds and waves.

Case 1 : for the heading angle control experiment, to verify the effect of gain parameters on the performance of the controller. the heading angle is controlled to rotate to 200 deg at a speed of 3.0 m/s. In the experiment, the initial heading angle of the USV is preset to almost 30 deg, and the parameters are set to c  = 5.0, q  = 0.2, K = 0.731, and T = 0.412, the maximum rudder angle is limited to 20 deg, and the maximum change rate is 6 deg per second. The change in the heading over time is observed and recorded under the control of the conventional discrete sliding mode heading controller based on the approach law (gain parameter ε   =   0.4 ⁠ ) and adaptive adjustment of the gain parameter ε of the discrete sliding mode heading controller based on the approach law. Figure 11 shows the experimental results.

Experimental results of heading angle control test 1: ( a ) heading angle and ( b ) rudder angle

Case 2 : to check the adaptability of the heading controller to parameter perturbation, the initial heading angle of the USV is preset to almost 30 deg, and the speed is set to approximately 4.5 m/s. In the experiment, the parameters are set to c  = 5.0 and q  = 0.2, and the FFRLS online identification algorithm is introduced on the basis of the gain parameter ε of the adaptive discrete sliding mode controller to identify the maneuverability index of the USV online so that the parameter matrices A and B of the controller could be adaptively adjusted online. Figure 12 shows the experimental results.

Experimental results of heading angle control test 2: ( a ) heading angle, ( b ) rudder angle, and ( c ) online identification results of K, T value

Figure 12 shows that after introducing the FFRLS online identification algorithm, the heading control effect has not changed significantly. This further shows that the design of the heading adaptive discrete sliding mode controller is insensitive to parameter changes when the actuator movement speed of the USV is limited.

4.3.1 Comparsion With the Conventional Discrete Sliding Mode Controller.

As listed in Table 7 , compared with the conventional discrete sliding mode controller, the system response speed can be improved by adaptively adjusting the parameter ε ⁠ . The introduction of the online identification link has not produced a significant improvement in the control, further demonstrating that the designed heading angle controller has certain adaptability to system parameter changes.

The Control effect evaluation index

For the course angle control experiment, to verify the effect of gain parameters on the performance of the controller, referred to as case 3: the heading is controlled to rotate to 100 deg at a speed of 3.0 m/s. In the experiment, the initial heading of the USV is preset to almost 22 deg, and the parameters are set to c  = 6.0, q  = 0.4.

The sideslip angle of the USV is calculated indirectly from the lateral speed v and longitudinal speed u ⁠ . However, due to factors such as sensor accuracy, the value of the sideslip angle is not stable, which has a greater impact on the online identification system. Therefore, the discrete sliding mode heading controller has adaptively adjusted for the gain parameter ε and the conventional discrete sliding mode controller. The experimental results are shown in Fig. 13 .

Experimental results of course angle control test 1: ( a ) course angle and ( b ) rudder angle

As presented in Fig. 13 and Table 8 , the discrete sliding mode course angle controller with the adaptively adjusted gain parameter ε yields a better control performance than the conventional discrete sliding mode heading controller.

Case 4 : In Sec. 4.3 , it has been verified that the introduction of parameter adaptive adjustment on the basis of the course discrete sliding mode controller based on conventional reaching law can improve the system response speed and control performance to a certain extent. In this case, the performance of the designed control algorithm is verified by an on-site real-ship experiment used to test further the effect of the designed course controller in practical applications.

In the experiment, the initial course of the USV is set to 10 degrees, and the maximum rudder angle is limited to 30 degrees. Then, control the course deflection to 60 degrees at a speed of about 3.0 m/s. Observe and record the course change over time of the USV under the three control methods of ADRC, gain parameter adaptive adjustment discrete sliding mode heading controller, and the introduction of online identification link. In this case, the experimental results are shown in Fig. 14 .

Experimental results of course angle control test 2: ( a )course angle responses, ( b ) results of online identification, and ( c ) rudder angle responses

For the above three sets of experimental results, the experimental data after the first arrival at the desired course are obtained to obtain their average deviation and standard deviation, the rise time t r ⁠ , and the adjustment time t s ⁠ , the specific results are shown in Table 9 .

Control effect evaluation index

It can be seen from the experimental results that the designed parameter adaptive discrete sliding mode controller has better control performance than the normal disturbance rejection control law.

4.4 Path Following Results.

Path-following experiments were performed to test and verify the performance of the proposed path following control method. As addressed in Sec. 3 , following the course angle with the constant velocity is the purpose of the path-following problem. When the tracking error is within the range of the length of the vessel(less than 7 m) in real sea, it can be considered as a great control effect.

Field test 1: We plan a path composed of straight lines to verify the practicability and stability of the path following controller, as shown in Fig. 15 . In test 1, Fig. 15(a) shows the path set in advance and the actual navigation track of the USV in the experiment. As shown in Fig. 15(b) , the maximum error at the corner is approximately 20 m, the stable error is within ± 5 m. After the stabilization, the tracking error is within the ship's length, which can meet the normal requirements of the path following task. The course angle and rudder angle of the USV were present in Figs. 15(c) and 15(d) .

Experimental results of the path following test 1: ( a ) predefined path and the responses, ( b ) position error, ( c ) desired heading angle and the responses, and ( d ) desired rudder angle and the responses

Field test 2: To test the control effect of the designed curve path following controller in an actual marine environment, the controller was applied to the USV. A circular reference path with a radius of 80 m and a sinusoidal reference path with an amplitude of 80 m was designed to verify the actual effect of the design curve path following controller. In the experiment, the maximum rudder angle was limited to 20   deg ⁠ , and the maximum change rate was 6   deg per second. Figure 16 shows the experimental results.

Experimental results of the path following test 2: ( a ) predefined path and the responses, ( b ) position error, ( c ) desired heading angle and the responses, and ( d ) desired rudder angle and the responses

As can be seen from Fig. 16 , in the actual marine environment, the USV can complete the curve path tracking task under the control of the designed curve path following controller. When tracking a circular path, the error is stable within ± 3 m. After the stabilization, the tracking error is within the ship's length, which can meet the normal requirements of the path following task. The proposed method performed well even when subjecting the USV to environmental disturbances.

This study proposes a multimodel control scheme-based path following controller for USVs. The uncertainties induced by complex environment disturbances contaminated in the sideslip angle are highlighted and investigated in-depth by introducing an online identification technique for control model parameters estimation and discrete siding model control method. The PSO incorporated with FFRLS is able to improve online identification outcomes. A series of case studies on identification technique, a multimodel course angle control scheme, and the hybrid controller combining the previously introduced two components, LOS and DSMC are carried out, for which the results demonstrate the expected performances. The proposed control system is convenient and flexible to make the desired changes depending on the navigation environment. In particular, the model combined with the online identification algorithm can effectively capture the complicated dynamics of the USV under the effects induced by environmental disturbances, etc. The proposed adaptive discrete sliding mode control algorithm ensures a collaborative control of the heading and course angles, where LOS guidance algorithm is combined to closely track the desired path.

Future works will focus on collision avoidance, path planning, and cooperative control of USVs, as part of our in-depth studies on the development of advanced autonomous vehicle systems.

The National Key Research and Development Program of China (Grant No. 2021YFC3101800; Funder ID: 10.13039/501100012166).

National Science Foundation of China (NSFC) (Grant No. U2141234).

Natural Science Foundation of Hainan Province of China (Grant No. 624MS079; Funder ID: 10.13039/501100004761).

The datasets generated and supporting the findings of this article are obtainable from the corresponding author upon reasonable request.

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