Multiple Surface Vessels Research Articles

Deep Reinforcement Learning-Enhanced Target Encirclement of Multiple Unmanned Surface Vessels

Target encirclement of multiple unmanned surface vessels (USVs) is a prevalent tactical strategy in maritime defense missions, significantly enhancing defense efficiency. However, challenges arise due to the limited collaborative capacity stemming from underutilized information within multi-USV systems during such tasks. In this context, a multi-USV target encirclement based on an improved multi-head attention Q-value mixing network is proposed. Initially, a reinforcement learning model tailored for USVs is designed, taking into account the complexities inherent in encirclement tasks. Subsequently, by incorporating distinct action semantics for value calculation, USVs are empowered to accurately assess action values, thereby improving decision-making processes. Leveraging the Qatten algorithm framework, a multi-USV target encirclement method with weighted action semantic-assisted value function decomposition is introduced. Comparative and ablation experiments conducted in uniform-speed target encirclement scenarios validate the effectiveness and high success rate of the proposed method.

Distributed observer-based position-based fuzzy formation control for unmanned surface vessels with input saturation

In this article, a control issue is investigated for achieving distributed formation forming and tracking of multiple unmanned surface vessels (USV) subjected to unknown model dynamics and external disturbance. Additionally, the constraints posed by the lack of velocity measurements and input saturation are considered for each USV. For this purpose, two types of distributed position-based control schemes are presented to constitute formation shape and track target trajectory by steering multiple USVs. The first control scheme is based on acquiring absolute position measurements and communication data, while the second control scheme relies on relative position measurements. In the two aforementioned control schemes, two different types of observers are scheduled to provide essential data support for the corresponding controllers. Then, the unknown data that include unknown model dynamics and external disturbance are approximated by a fuzzy logic system and adaptive laws, respectively. In addressing the issue of controller input saturation, a smooth function and auxiliary system are imported to eliminate the effect of actuator saturation. Finally, suitable Lyapunov functions are selected to analyze the theoretical feasibility of the two designed schemes. Corresponding digital simulations are exhibited to further examine the robustness and effectiveness of the designed control schemes.

Fixed-time event-triggered sliding mode time-varying formation control for multiple surface vessels with fast convergence

ABSTRACT This paper proposes a new fixed-time sliding mode time-varying formation control strategy for multiple surface vessels (MSVs) to improve control performance and ensure navigation safety. First, a fixed-time extended state observer (FxESO) is designed to provide estimations of velocities and lumped disturbances. Then, the event-triggered fixed-time distributed time-varying formation control law is designed based on prescribed performance function (PPF) and fixed-time nonsingular terminal sliding mode (FxNTSM) manifold. Finally, system stability is analyzed based on Lyapunov theory. The salient features of the proposed scheme are as follows. First, a novel hyperbolic cosecant PPF is incorporated into the control scheme to enhance control performance. Then, the proposed scheme is combined with relative threshold event-triggered strategy to reduce unnecessary updates of actuators. Finally, a uniform exact differentiator is introduced to avoid the formation control law including the acceleration of adjacent vessel. Comparative results are given to demonstrate the superiority of the proposed scheme.

Differential graphical games of multiagent systems with nonzero leader's control input and external disturbances

AbstractIn this article, we investigate the problem of differential graphical games for multiagent systems (MASs) with external disturbances. In particular, the system considered in this article allows the leader to have an unknown bounded control input, and the communication topology between agents is allowed to be a weakly restricted structure with only containing a directed spanning tree. We propose a novel dynamic sliding mode control strategy to dispose the presence of leader's nonzero control input and external disturbances. Furthermore, a nominal controller based on the worst‐case control strategies of neighbors is designed to provide a distributed solution for differential graphics games of MASs. Finally, our algorithms are applied to solve multiple unmanned surface vessels games. Simulation studies are provided to test the effectiveness of the proposed algorithms.

Adaptive neural bounded formation tracking control of multiple autonomous surface vessels subject to actuator saturation and faults

Adaptive neural bounded formation tracking control of multiple autonomous surface vessels subject to actuator saturation and faults

Time-varying formation for MSVs with input and prescribed performance constraints by fixed-time event-triggered sliding mode control

Time-varying formation for MSVs with input and prescribed performance constraints by fixed-time event-triggered sliding mode control

Collaborative Parameter Estimation of Multiple Unmanned Surface Vessels: A Robust Distributed Estimator-Based Approach

In this paper, the collaborative parameter estimation of multiple unmanned surface vessels (USVs) with model structure uncertainties is studied. The considered parameter estimation problem is first converted into a distributed state and parameter joint estimation problem. Then, the robust distributed estimator is constructed to handle the inevitable model structure uncertainties, and the upper bounds of prediction and estimation error covariance matrices are derived respectively. Additionally, the upper bound of the estimation error covariance matrix is minimized by designing appropriate estimator gains. Finally, the advantages of the proposed distributed parameter estimation approach from the perspectives of information interaction and consideration of model structure uncertainties are verified via simulations and practical experiments.

Distributed Robust Learning Control for Multiple Unmanned Surface Vessels With Fixed-Time Prescribed Performance

Distributed Robust Learning Control for Multiple Unmanned Surface Vessels With Fixed-Time Prescribed Performance

Adaptive Optimal Surrounding Control of Multiple Unmanned Surface Vessels via Actor-Critic Reinforcement Learning.

In this article, an optimal surrounding control algorithm is proposed for multiple unmanned surface vessels (USVs), in which actor-critic reinforcement learning (RL) is utilized to optimize the merging process. Specifically, the multiple-USV optimal surrounding control problem is first transformed into the Hamilton-Jacobi-Bellman (HJB) equation, which is difficult to solve due to its nonlinearity. An adaptive actor-critic RL control paradigm is then proposed to obtain the optimal surround strategy, wherein the Bellman residual error is utilized to construct the network update laws. Particularly, a virtual controller representing intermediate transitions and an actual controller operating on a dynamics model are employed as surrounding control solutions for second-order USVs; thus, optimal surrounding control of the USVs is guaranteed. In addition, the stability of the proposed controller is analyzed by means of Lyapunov theory functions. Finally, numerical simulation results demonstrate that the proposed actor-critic RL-based surrounding controller can achieve the surrounding objective while optimizing the evolution process and obtains 9.76% and 20.85% reduction in trajectory length and energy consumption compared with the existing controller.

Distributed Leader Escort Control for Multiple Autonomous Surface Vessels: Utilizing Signed Graph to Model Interaction Relationships

Distributed Leader Escort Control for Multiple Autonomous Surface Vessels: Utilizing Signed Graph to Model Interaction Relationships

Cooperative Adaptive Tracking Control Based on Quantized States for Multiple Surface Vessels

Cooperative Adaptive Tracking Control Based on Quantized States for Multiple Surface Vessels

Adaptive output-constrained finite-time formation control for multiple unmanned surface vessels with directed communication topology

Adaptive output-constrained finite-time formation control for multiple unmanned surface vessels with directed communication topology

Two‐layer leader‐follower optimal affine formation maneuver control for networked unmanned surface vessels with input saturations

AbstractThis article studies the two‐layer leader‐follower optimal affine formation maneuver (AFM) control problem for multiple unmanned surface vessels (USV). The basic idea of the developed two‐layer control framework is to realize the time‐varying formation for the leader group in advance, and then let the follower USVs agilely respond to the target formation affinely localized by leaders. To realize this goal, a time‐varying formation reference system is first synthesized to describe leaders' target formation in the affine map of the nominal configuration. The reference system is set up by virtual vessel velocity command and unrotated geometric command, which make it possesses an intuitive application structure for operators to plan AFM commands in real‐time sensed surrounding environments. Then, by means of optimized backstepping design and the adaptive dynamic programming technique, actor‐only reinforcement learning controllers are established for USVs in both two layers to realize the optimal target formation tracking objective. For the proposed optimal controllers, the persistent excitation condition that is required by common optimal control schemes is also removed, which endows the presented scheme with lower computational complexity. Finally, theoretical analysis and simulation results illustrate the closed‐loop stability and the effectiveness of the presented scheme.

Distributed edge-based event-triggered optimal formation control for air-sea heterogeneous multiagent systems

Distributed edge-based event-triggered optimal formation control for air-sea heterogeneous multiagent systems

Containment control of multiple unmanned surface vessels with NN control via reconfigurable hierarchical topology.

This paper investigates the containment control of multiple unmanned surface vessels with nonlinear dynamics. To solve the leader-follower synchronization problem in a containment control system, a hierarchical control framework with a topology reconfiguration mechanism is proposed, and the process of containment control is converted into the tracking of a reference signal for each vessel on its respective target heading by means of the light-of-sight (LOS) guidance. In a control system, the neural networks (NNs) are adopted to consider the uncertainty. In the follower layer, a connectivity controller with a topology reconfiguration mechanism is embedded, to change the converging positions of followers so as to avoid collision within the system, and to maintain the system connectivity when the communication equality is poor. The effectiveness of the hierarchical control framework proposed in this paper is valid by simulation.

Fixed-Time Formation Tracking Control of Multiple Unmanned Surface Vessels Considering Lumped Disturbances and Input Saturation

This paper investigates the challenging problem of fixed-time formation trajectory tracking control for multiple unmanned surface vessels (USVs) affected by uncertain model dynamics, time-varying external ocean disturbances, as well as input saturation. Firstly, an adaptive super-twisting lumped disturbance observer (ASTLDO) is created by integrating high-order sliding mode with observer technology, which can accurately observe and compensate for the complex disturbance of the system within a finite time. Secondly, following the disturbance observer, backstepping technique, fixed-time control, and virtual leader–follower algorithm, the fixed-time formation tracking strategy is implemented. The proposed formation tracking control scheme enables the multiple surface vessels system to converge and maintain a stable desired formation in a fixed time, and the convergence time is independent of the initial states of the system. Furthermore, an adaptive auxiliary system is introduced to mitigate input saturation. In the end, the effectiveness and anti-interference ability of the suggested approach are confirmed by the formation simulation results of three USVs.

Event-Triggered Finite-Time Formation Control of Underactuated Multiple ASVs with Prescribed Performance and Collision Avoidance.

In this paper, an event-triggered finite-time controller is proposed for solving the formation control problems of underactuated multiple autonomous surface vessels (ASVs), including asymmetric mass matrix, collision avoidance, maintaining communication distances and prescribed performance. First, to not only avoid collisions between the follower and leader but also maintain an effective communication distance, a desired tracking distance is designed to be maintained. Second, an improved barrier Lyapunov function (BLF) is proposed to implement the tracking error constraint. In addition, the relative threshold event-triggering strategy effectively solves the communication pressure problem and greatly saves communication resources. Finally, based on coordinate transformation, line of sight (LOS) and dynamic surface control (DSC), a comprehensive finite-time formation control method is proposed to avoid collisions and maintain communication distance. All the signals of the proposed control system can be stabilized in finite time (PFS). The numerical simulation results verify the effectiveness of the proposed control system.

Finite-Time Output Feedback Cooperative Formation Control for Marine Surface Vessels With Unknown Actuator Faults

This article studies the finite-time output-feedback cooperative formation problem of multiple marine surface vessels (MSVs) without using velocity information, where each MSV contains unknown time-varying actuator faults, ocean disturbances, and model uncertainties. Considering the performance specifications and requirements in practice, the formation errors and velocities are also required to change in a predefined compact set. Aiming at the challenge of unknown input gain caused by unknown time-varying multiplicative faults, a novel nonlinear extended state observer with an adaptive law is first constructed, which cannot only recover unmeasurable velocities from position-heading information but also simultaneously compensate for ocean disturbances, model uncertainties, and additive faults. Subsequently, combining the barrier Lyapunov function and the nonlinear tracking differentiator technique, a unified finite-time output-feedback cooperative control framework is developed, including both kinematics and kinetics, to prevent constraint deviation and avoid the computational complexity of the traditional backstepping method. Using finite-time stability theory, the designed output feedback cooperative controller can ensure that the desired cooperative performance is achieved within a finite time and tracking errors converge to a small neighborhood of the origin while ensuring that the closed-loop system is semiglobally uniformly ultimately bounded. Simulation examples are shown to demonstrate the effectiveness of the proposed control scheme.

Adaptive bipartite tracking control for multiple autonomous surface vessels

Adaptive bipartite tracking control for multiple autonomous surface vessels

Event-triggered fixed-time distributed output feedback sliding mode cooperative control for multiple surface vessels with input saturation

Aiming at the problems of cooperative control for multiple surface vessels (MSVs), such as unknown environmental disturbances, unavailable velocities, model uncertainties, actuator saturation, and limited action times of the actuator, an event-triggered fixed-time distributed output feedback sliding mode cooperative control method with input saturation is proposed. The scheme ensures the practical fixed-time stability of the cooperative control system. First, 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. Second, to deal with the actuator saturation, a fixed-time auxiliary dynamic system is designed. Third, a fixed-time non-singular terminal sliding mode manifold (FxNTSMM) is introduced to effectively eliminate singularity and improve chattering of the system. Finally, an event-triggered distributed controller based on FxNTSMM and FxESO is proposed. An event-triggered condition can avoid unnecessary actions of the actuator, and Zeno phenomenon is avoided by theoretical proof. In addition, the upper bound of the convergence time is independent of the initial state. Simulation results are given to demonstrate the effectiveness of the proposed control scheme.