Simplified optimised prescribed performance control for high-order multiagent systems with privacy preservation

Abstract

This paper studies the consensus tracking problem based on optimised backstepping technique for multiagent systems with power exponential functions and the privacy protection. Under the optimised backstepping technique, the controllers with power functions are designed by utilising the reinforcement learning strategy. Moreover, the synchronisation error converges to a predetermined region within a user-defined settling time by utilising a speed function. To ensure the safety of communication, the privacy protection is applied to multiagent systems, which effectively prevent information exposure. Based on Lyapunov stability theory, the tracking errors of the system with power exponential functions converge to a predetermined region, and a simulation example proves the feasibility of the proposed strategy.