A Q-Learning-Based Parameters Adaptive Algorithm for Formation Tracking Control of Multi-Mobile Robot Systems

This paper proposes an adaptive formation tracking control algorithm optimized by Q-learning scheme for multiple mobile robots. In order to handle the model uncertainties and external disturbances, a desired linear extended state observer is designed to develop an adaptive formation tracking control strategy. Then an adaptive method of sliding mode control parameters optimized by Q-learning scheme is employed, which can avoid the complex parameter tuning process. Furthermore, the stability of the closed-loop control system is rigorously proved by means of matrix properties of graph theory and Lyapunov theory, and the formation tracking errors can be guaranteed to be uniformly ultimately bounded. Finally, simulations are presented to show the proposed algorithm has the advantages of faster convergence rate, higher tracking accuracy, and better steady-state performance.

Event-Triggered Formation Tracking Control for Unmanned Aerial Vehicles Subjected to Deception Attacks

This study investigates the time-varying formation tracking (TVFT) control problem for multiple unmanned aerial vehicle (multi-UAV) systems under deception attacks by utilizing an event-triggered mechanism (ETM). First, for the sake of alleviating the communication burden, an effective ETM is designed in this paper. Second, to deal with deception attacks in the communication network, a random deception attack model under the designed ETM is constructed. Finally, a novel formation tracking control scheme for multi-UAV systems under deception attack combining the ETM is proposed to achieve the expected TVFT. The stability analysis of the formation control system is given by using the Lyapunov stability theory and linear matrix inequality (LMI) technique. Simulations are conducted to verify the effectiveness of the proposed formation control scheme.

Time-varying output formation-tracking of heterogeneous multi-agent systems with time-varying delays and switching topologies

This paper focuses on the time-varying output formation (TVOF) tracking control of heterogeneous linear multi-agent systems (HL-MASs) with both delays and switching topologies, where the followers’ outputs can move along the reference trajectory generated by the leaders and maintain the desired time-varying formation. First, a distributed observer is proposed for each follower, aiming to estimate the convex combination of leaders’ state with both communication delays and switching graphs. The observer’s error for heterogeneous MASs is analyzed based on Lyapunov theory and linear matrix inequality (LMI) technique. Second, the observer is incorporated into the output formation tracking protocol. Then, an algorithm is put forward to calculate the control feedback gains and the formation tracking feasibility constraint is also provided. Furthermore, the convergence of the formation tracking error is proved. At last, the effectiveness of this proposed method is validated through a numerical simulation.