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

Abstract

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 leaderfollower 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 eventtriggered coordinated trajectory tracking control (ETCTTC) system gradually converge to zero, and Zeno behavior is avoided. The theoretical results are verified by simulations.

Event-triggered robust adaptive control for unmanned surface vehicle in presence of deception attacks

“…Therefore, it has great significance to develop the event-triggered mechanism (ETM) for enhance theoretical algorithms practicality. In view of the above analysis of the control characteristics of USV systems, adaptive event-triggered control algorithms [15][16][17] have been proposed to solve the problems of communication load and network attacks. Moreover, Mahmoud and Hamdan 18 designed an observer-based controller to deal with deception attacks against conditional probability variable, although taking into account attacks on the network between controllers and actuators, cyber-attacks on channels can also invalidate theoretical algorithms.…”

Distributed Dynamic Event-Triggered Formation Control for Multiple Unmanned Surface Vehicles

“…In view of this, the control algorithm theoretically needs to eliminate the Zeno phenomenon. In preliminary work, static event-triggered communication schemes [17][18][19][20] have been continuously investigated with the aim of reducing the frequency of communication while ensuring consensus. For instance, in [18], a compensatorbased command-filtered formation control algorithm is proposed, and an event-triggering communication strategy is developed to govern the communications between the leader AUV and follower AUVs.…”

“…For instance, in [18], a compensatorbased command-filtered formation control algorithm is proposed, and an event-triggering communication strategy is developed to govern the communications between the leader AUV and follower AUVs. Using the same approach to dealing with wasted communication resources as presented in the literature [18], a distributed eventtriggered adaptive coordinated trajectory tracking controller for multiple unmanned surface vehicles is proposed in [17], based on the undirected communication topology. As a technical extension of this result, the fixedtime control method is introduced to design the event-based distributed formation controller for time-oriented missions [19] .…”

“…Because the event-triggered scheme can be implemented successfully, each USV only needs to obtain the status of neighbors at a specific trigger moment. Compared with the static event-triggered control [17][18][19][20], the trigger time interval of this triggering scheme has significantly increased.…”

Adaptive Leader-Following Consensus Tracking Control of Multiple UAVs Subject to Deception Attacks

“…In recent years, the cooperative control issues of multi-unmanned aerial vehicle (UAV) systems have attracted considerable attention from scientific and engineering fields [1][2][3][4][5][6][7][8], mainly owing to the fact that a group of mobile UAVs come to agreement by utilizing local relative information from adjacent UAVs, which can cooperate to complete some complex tasks that exceed the capability of a single vehicle. Additionally, a group of UAVs has better robustness than a single vehicle when executing tasks.…”