Adaptive Practical Optimal Time-Varying Formation Tracking Control for Disturbed High-Order Multi-Agent Systems

The adaptive practical optimal time-varying formation tracking problems of the disturbed high-order multi-agent systems with a noncooperative leader are considered. Different from the former achievements, the effects of the leader’s unknown control input and followers’ external disturbances are both considered in the optimal time-varying formation tracking issues. Firstly, an adaptive practical optimal time-varying formation tracking protocol is proposed. The extended state observers and adaptive neural networks are introduced to estimate the integrated uncertainty and value function for the adaptive protocol, respectively. Then, an algorithm is presented to determine the control parameters for the adaptive optimal protocol and neural networks weights update laws. Thirdly, the stability and the optimal formation tracking property are analyzed for the closed loop disturbed high-order multi-agent system. Finally, the numerical simulation results are presented for revealing the effectiveness of the obtained theoretical methods.