Multiple Surface Vessels Research Articles

Flexible Formation Tracking Control of Multiple Unmanned Surface Vessels for Navigating Through Narrow Channels with Unknown Curvatures

This article proposes a flexible formation tracking control protocol (FFTC) for multiple unmanned surface vessels (USVs) to pass through narrow water channels with unknown curvatures. An observer is developed to estimate the curvatures of channels. A flexible formation tracking control protocol is, thereby designed to steer USV fleets to pass through narrow channels in a flexible serial formation. Furthermore, the asymptotically stable conditions of the closed-loop multi-USV systems are theoretically derived. Finally, both numerical simulation and experimental results with a fleet of three HUSTER-0.3 USVs are reported to substantiate the effectiveness of the proposed FFTC protocol for navigating through narrow channel in a laboratory context.

Nonsingular Terminal Sliding Mode-Based Distributed Cooperative Event-Triggered Control for Multiple Surface Vessels Under Actuator Faults With Input Saturation

In this paper, a fixed-time distributed cooperative control under actuator faults with input saturation scheme is designed for multiple surface vessels (MSVs). Firstly, a fixed-time disturbance observer (FxDO) is introduced to observe unknown environmental disturbances and actuator faults (AF). Secondly, to deal with the actuator saturation, an improved nonlinear antiwindup compensator is introduced to compensate for the saturation effect of the actuator. Thirdly, a fixed-time fault-tolerant event-triggered control law with the actuator saturation is applied to cooperative control based on a fixed-time nonsingular terminal sliding mode manifold (FxNTSMM), and their cooperative errors can converge within fixed time. At the same time, the upper bound of convergence time is independent of the initial state. Finally, the stability analysis of the cooperative control system is given to prove that the system can realize the practical fixed time stability, and Zeno phenomenon is avoided by theoretical proof. Simulation results are given to demonstrate the effectiveness of the proposed control scheme.

Fixed-Time Output Feedback Distributed Cooperative Event-Triggered Control for Multiple Surface Vessels With Prescribed Performance Constraints

This paper studies the distributed cooperative control problem for multiple surface vessels (MSVs) subject to unknown environmental disturbances, model uncertainties, unavailable velocities and prescribed performance constraints. Firstly, a fixed-time extended state observer (FxESO) is designed to provide the estimations of velocities and lumped disturbances (including unknown environmental disturbances and model uncertainties). Secondly, to improve the convergence performance of the MSVs, a hyperbolic cosecant prescribed performance function is incorporated into the cooperative control algorithm. Thirdly, a fixed-time event-triggered control law with prescribed performance constraint is applied to cooperative control based on a fixed-time nonsingular terminal sliding mode manifold (FxNTSMM), and the cooperative errors can converge within fixed time. Finally, by employing Lyapunov function theory, the stability of the closed-loop system is analyzed. Simulation results are given to demonstrate the effectiveness of the proposed control scheme.

Distributed adaptive fixed-time formation control for UAV-USV heterogeneous multi-agent systems

This paper investigates formation trajectory tracking control for heterogeneous multi-agent systems with external disturbances, model uncertainties and input saturation. The system that is considered comprises one unmanned aerial vehicle (UAV) and multiple unmanned surface vessels (USVs). First, based on directed graph theory, a distributed formation control protocol is proposed for the UAV-USV heterogeneous multi-agent system. Second, combining the advantages of the adaptive technique and radial basis function (RBF) neural networks, a global fixed-time adaptive neural network nonsingular fast terminal sliding formation control protocol is designed to ensure tracking of the desired trajectory and form the predetermined formation configuration within a fixed time in the presence of various uncertainties. Through the proposed adaptive neural network (NN) control technology, the lumped uncertainty can be estimated, and the number of update parameters can be reduced, thereby relieving the calculation burden of the controllers. In addition, a dynamic event-triggered mechanism is incorporated into the controllers, which can reduce the update frequency of controllers, thereby decreasing the communication number of controllers. A saturation function is introduced simultaneously to solve the problem of input saturation. Finally, the simulation results are given to indicate the feasibility of the proposed formation control protocol.

Cooperative strategy for pursuit-evasion problem with collision avoidance

This paper presents a self-organizing cooperative pursuit strategy for multiple unmanned surface vessels (USVs) to pursuit an intelligent evader in the open water. Firstly, the escape strategies of intelligent evaders under different encirclement states and the distribution of pursuers formed according to Apollonius circle are described. Then, in order to achieve the conditions of successful encirclement, a flexible self-organizing cooperation strategy is proposed to form the encirclement formation. In order to better achieve the obstacles encountered in the process of pursuing in the actual environment, the obstacle avoidance methods of irregular obstacles are presented. The simulation results show that the proposed strategy can enable the pursuit USV swarm to capture the intelligent evader, and the pursuit swarm has good obstacle avoidance performance and flexibility.

Vector acoustic properties of the underwater sound field from multiple, simultaneously observed ships

Vector acoustic properties of the underwater sound field simultaneously observed from multiple surface vessels during the recently completed (May–June 2022) experiment on the New England Mud Patch (NEMP) approximately 100 km south of Cape Cod are discussed. The properties, such as bearing, degree of polarization, and other non-dimensional parameters are derived from a 4 by 4 field matrix composed of pressure and 3-component velocity, and a 3 × 3 matrix composed of only velocity components. The measurements were made with two sensing systems, separated by 21 km, referred to as an Intensity Vector Autonomous Recorder (IVAR), and identified as IVAR-1 and IVAR-2. Individual ship CPAs tracks are identified with automated ship identification (AIS) data. In this presentation, the two sources of measured vector acoustic field data combined with the AIS data are exploited to study the effect of interaction of multiple acoustic sources on a received vector field.

Terminal sliding-mode disturbance observer-based finite-time adaptive-neural formation control of autonomous surface vessels under output constraints

AbstractThis paper proposes a tracking controller for the formation construction of multiple autonomous surface vessels (ASVs) in the presence of model uncertainties and external disturbances with output constraints. To design a formation control system, the leader-following strategy is adopted for each ASV. A symmetric barrier Lyapunov function (BLF), which advances to infinity when its arguments reach a finite limit, is applied to prevent the state variables from violating constraints. An adaptive-neural technique is employed to compensate uncertain parameters and unmodeled dynamics. To overcome the explosion of differentiation term problem, a first-order filter is proposed to realize the derivative of virtual variables in the dynamic surface control (DSC). To estimate the leader velocity in finite time, a high-gain observer is effectively employed. This approach is adopted to reveal all signals of the closed-loop system which are bounded, and the formation tracking errors are semi-globally finite-time uniformly bounded. The computer simulation results demonstrate the efficacy of this newly proposed formation controller for the autonomous surface vessels.

Self-Organizing Cooperative Pursuit Strategy for Multi-USV with Dynamic Obstacle Ships

A self-organizing cooperation strategy for multiple unmanned surface vessels (USVs) to pursue intelligent evaders in the case of a dynamic obstacle vessel is proposed. Firstly, a self-organizing cooperative hunting strategy is proposed to form an Apollonius circle. According to the escape strategies of evaders under different encirclement states, the pursuers are divided into pursuit group and ambush group. The pursuit group drives the evaders into the ambush area and completes the encirclement together with the ambush group. In order to better deal with the dynamic obstacle ships encountered in the pursuit process in the dynamic ocean environment, the artificial potential field-based collision avoidance method for inter-USV and dynamic collision avoidance strategy for encountering obstacle ships based on International Regulations for Preventing Collisions at Sea (COLREGs) are proposed. The simulation results show that the algorithm can make the pursuers complete the encirclement of the evaders and has good obstacle avoidance performance and flexibility in the environment with dynamic obstacle ships.

Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence

In recent years, the research of multiple unmanned surface vessels collaboration has received great attention. More and more researchers have proposed different methods of multiple unmanned surface vessels collaboration, such as cooperative collision avoidance, formation, and rendezvous. Based on the significant advantages of biological swarm intelligence applications in these collaborative methods, this article summarizes the research methods of multiple unmanned surface vessels collaborative search and hunting from the perspective of swarm intelligence. First of all, this article summarizes the key technologies of multiple unmanned surface vessels collaborative search and hunting from the aspects of the multi-robot system, group communication, environment modeling, collaboration mechanism, and path planning. Then, it reviews some classic swarm intelligence algorithms, analyzes the advantages and disadvantages of these algorithms, and proposes optimization directions for existing disadvantages based on relevant literature. Finally, the article points out some existing problems in every stage and suggestions for future research.

Location Game of Multiple Unmanned Surface Vessels With Quantized Communications

A placement problem of multiple unmanned surface vessels (USVs) is investigated from a game perspective in this brief. The group of USVs is required to form a desired formation shape, while each USV has its individual objective of being at a particular place relative to the static reference target according to its own benefit. Note that the individual goals of USVs may conflict with the global formation goal of the group. In this context, the location game of multiple USVs is formulated, and a gamed-based controller is designed for each USV to drive it to the equilibrium position that balances the formation goal and the individual goal. Moreover, considering practical limited communication bandwidth, the transmitted information of the USVs is quantized through a uniform quantizer. It is proved that there exists a unique Nash equilibrium of the location game of multiple USVs and the designed controller can drive the USV systems with quantized communication to a small neighborhood of the Nash equilibrium.

Time-varying formation control of multiple unmanned surface vessels with heterogeneous hydrodynamics subject to actuator attacks

This paper studies the time-varying formation for multiple unmanned surface vessels (USVs) with heterogeneous hydrodynamics under actuator attacks. Firstly, the distributed time-varying formation is achieved under a formation feasibility condition. Secondly, an extended state observer (ESO) is devised to estimate the heterogeneous hydrodynamics and the external time-varying disturbance of multiple USVs, as well as the unknown control input of the leader USV simultaneously based on the neighbor USVs’ relative information; Thirdly, a distributed security controller is jointly designed based on the relative information of neighbors with the presence of an additive adaptive correction term to suppress the effects of actuator attacks instead of redesigning the nominal controller; Finally, the effectiveness of the derived theoretical method is demonstrated by simulation results.

Distributed optimization for coordinated dynamic positioning of multiple surface vessels based on asymptotically stable ESOs

This paper presents a distributed optimization method for coordinated dynamic positioning (CDP) of multiple unmanned surface vessels (USVs) subject to uncertainties and disturbances. The control objective is to achieve a relative dynamic positioning of multiple USVs with the optimal position encoded in a sum of local functions. Two types of distributed schemes featured as coupled and decoupled optimization and control are presented. By incorporating a robust integral of sign of the error into an extended state observer (ESO) design, a robust distributed control law is designed for each vessel based on its local cost function at first. Next, another distributed control law with decoupled optimization and control is presented. It consists of a high-level distributed optimizer and a low-level robust position tracking control law based on a backstepping technique and asymptotically stable ESOs. By using the proposed method, the sum of the cost functions of all USVs under a connected network is minimized and a relative formation is achieved despite uncertainties and disturbances. Simulation results are provided to illustrate the effectiveness of the proposed distributed-optimization-based control laws for CDP of multiple USVs.

Robust formation tracking of multiple autonomous surface vessels with individual objectives: A noncooperative game-based approach

Distributed robust formation tracking of multiple autonomous surface vessels (ASVs) with uncertain dynamics and individual objectives is investigated in this paper by developing a noncooperative game-based approach. Compared with the multiple ASVs model commonly studied in existing literature, two distinct features of the present multiple ASVs model are: (i) the ASVs are allowed to have individual objectives, and (ii) the evolution of each ASV is subjected to unmodeled dynamics and time-varying external disturbances. Specifically, the ASVs are required to cooperatively achieve the group objective of tracking a time-varying reference trajectory in a specific formation pattern, while each ASV also needs to complete its own individual objective of maintaining desired displacement with respect to the reference trajectory during the formation tracking process according to its own benefit. A noncooperative game-based approach is developed for the ASVs to achieve the goal of formation tracking in the presence of individual objectives where the formation tracking problem is cast into the Nash equilibrium seeking problem of a noncooperative game among ASVs subject to unmodeled dynamics and external disturbances. To make each ASV seek the Nash equilibrium efficiently, adaptive neural network (NN) is adopted to approximate the unmodeled dynamics and nonsmooth feedback is utilized to deal with the effect of bounded external disturbances. It is theoretically shown that the states of ASVs including the position and heading angle states could asymptotically converge to the Nash equilibrium if the underlying communication graph is strongly connected and the control parameters of the Nash equilibrium seeking algorithms are suitably selected. Finally, an experimental study is performed to verify the validity of the theoretical results.

Collaborative exploration of multiple unmanned surface vessels in complex areas based on PPO algorithm

The increasing congestion of maritime traffic leads to frequent maritime traffic accidents. Unmanned search and rescue equipment provides a guarantee for rapid rescue operations. In marine accidents, the waiting time is short and the rescue risk factor is high. Unmanned surface vessel (USV) can transport rescue equipment to the accident site in the first time and carry out searching and rescuing, which will greatly improve rescue efficiency. With the development of technology, USV can autonomously conduct area exploration to assist in the discovery of survivors. This paper proposes a complex area exploration of multiple unmanned surface vessels based on the Proximal Policy Optimization algorithm (PPO). The PPO algorithm is used to improve training efficiency, achieve 100% search coverage in complex water surface areas, and make searching and rescuing operations safe, simple and efficient. Experimental simulations show that the algorithm can realize 100% area exploration, have high search efficiency, and consumes less energy. This is a new intelligent ship application that can complete 100% exploration without human involvement.

Decentralized event-triggered cooperative path-following control for multiple autonomous surface vessels under actuator failures

This paper investigates the problem of cooperative path-following control for underactuated autonomous surface vessels in the presence of the model uncertainties, environmental disturbance, actuator failures and limited communication. A novel intelligent controller is designed for autonomous surface vessels to track priori parameterized reference paths so that the desired formation can be achieved. In the algorithm, the model uncertainties are estimated by neural networks. By virtue of the dynamic surface control technique, the inherent problem ”explosion of complexity” occurred in the traditional Backstepping design framework is avoided. A concise adaptive law is developed to compensate the upper bound of the weight matrix for neural networks, rather than the whole weight matrix. Furthermore, the event-triggered mechanism is embedded into the cooperative controller to reduce the frequency of inter-vehicle communication. The cooperative controller is updated only at the instant when the threshold condition is violated. By using the Lyapunov theory, both the semi-globally uniformly ultimately bounded and fault-tolerance capability of the closed-loop system are guaranteed. Finally, numerical examples are performed to demonstrate the effectiveness and superiority of the proposed algorithm.

Bearing-Only Motional Target-Surrounding Control for Multiple Unmanned Surface Vessels

This article proposes a distributed bearing-only controller for multiple unmanned surface vessels (USVs) to encircle and rotate evenly around a motional target with inter-USV topologies. The distributed control law consists of three terms, i.e., a bearing-only estimation term to approximate the target state, an upper-level surrounding term to fulfill the target-surrounding mission, and a single-vessel regulation term to track the upper-level signal. Significantly, technical conditions are derived to guarantee the asymptotical stability of the closed-loop system. Finally, experimental results on a real platform composed of three HUSTER-0.3 USVs and a target vessel are conducted to substantiate the effectiveness of the proposed controller.

Distributed Surrounding Control of Multiple Unmanned Surface Vessels With Varying Interconnection Topologies

In this brief, a distributed surrounding control problem is investigated for multiple unmanned surface vessels (USVs) with varying interconnection topologies. A distributed estimation-and-control hierarchical framework is developed, where an individual estimator is designed for a USV to predict the state of the target in an interconnection network with jointly dwellingly connected topologies. Thereby, the vessels could be governed to encircle the target in a convex hull, which evenly rotate around the target at the center. Moreover, asymptotical stability conditions are derived to guarantee the feasibility of the proposed surrounding controller. Finally, experiments are conducted for a real multi-USV system consisting of three 1.6 meters-long vessels and a differential GPS station, to verify the effectiveness of the proposed controller.

Distributed Event-Triggered Adaptive Coordinated Trajectory Tracking Control of Multi-USVs Based on the Aggregate Tracking Error

Aiming to solving the nonlinear coordinated trajectory tracking control problem of multi-USVs under the influence of slowly changing and uncertain environmental disturbances, reducing energy consumption and ensuring tracking performance and stability, a distributed event-triggered adaptive coordinated trajectory tracking controller (DET-ACTTC) for multiple unmanned surface vessels (multi-USVs) is proposed based on the undirected communication topology. By introducing a virtual leader, a leader-follower formation is used to generate the coordinated tracking errors. Based on the expected formation and states, the aggregate tracking errors are defined, and event-triggered measurement errors are constructed to design the event-triggered conditions. An adaptive term is used to compensate for external environment disturbances, and the DET-ACTTC is deduced for each USV in the group. The tracking errors of the event-triggered coordinated trajectory tracking control (ETCTTC) system gradually converge to zero, and Zeno behavior is avoided. The theoretical results are verified by simulations.

Cooperative formation control for multiple surface vessels based on barrier Lyapunov function and self-structuring neural networks

This paper studies the cooperative formation control problem of multiple surface vessels based on the barrier Lyapunov function and self-structuring neural networks with uncertainties and unknown disturbances. To constrain and prevent a consistency error that is too large, a tan-type barrier Lyapunov function is employed to dynamically restrain the formation of tracking errors. To handle the model uncertainties, self-structured neural networks are used to approximate the unknown parameters of the dynamics model and to avoid large computational burden. An adaptive law is developed to estimate and compensate for unknown disturbances and neural network approximation errors. Under the proposed distributed cooperative formation control law, formation behavior among vessels can be achieved through any directed communication topological network and an inaccurate model of each vessel. All signals in the closed-loop system are proven to be semi-globally uniformly ultimately bounded on the initial bounded conditions, and the formation tracking error converges to a small neighborhood of origin. The simulations evaluate the performance of the proposed controller, and verify the effectiveness of the proposed method.

Tracking Multiple Surface Vessels With an Autonomous Underwater Vehicle: Field Results

This article describes the development and testing of a passive sonar, multitarget tracker, and adaptive behavior that enable an autonomous underwater vehicle (AUV) to detect and actively track nearby surface vessels. A planar hull-mounted hydrophone array, originally designed for active sonar, is repurposed for passive sonar use and provides acoustic data to a time-delay-and-sum beamformer that generates multiple angle-only contacts. A particle filter tracker assimilates these contacts with a single-hypothesis data association strategy to estimate the position and velocity of targets. Summary statistics of each track are periodically reported to an onboard database along with qualitative labels. To improve tracking performance, detections trigger an adaptive behavior that maneuvers the AUV to maintain multiple targets in the field of view by minimizing the worst case aspect angle deviation from broadside (across all targets). The tracking system is demonstrated through at-sea experiments in which a Bluefin-21 AUV adaptively tracks multiple surface vessels, including another autonomous platform, in the approaches to Boston Harbor.