Prescribed-time Distributed Model Reference Adaptive Control for Nonlinear Multi-agent Systems
摘要
The control of nonlinear leader-followers system with closed-loop reference model (CRM) is considered in this paper. A model reference adaptive controller has been designed for the leader-followers system within prescribed-time convergence achievement. First, a prescribed-time adaptive observer is designed to reduce the impact of disturbances on the system. Further, the event-triggered and data-sampled event-triggered communication modes are adopted among the followers and leader-followers, respectively. Based on the observed states and shared leader state, a distributed model reference adaptive control strategy (MRAC) is developed to achieve the system convergence within the prescribed time. Moreover, the impact of the gain matrix of the feedback term in CRM on the convergence of the system is analyzed. A comparison experiment results between the CRM and open-loop reference model validate that the MRAC with CRM can improve the convergence of the leader-followers system. Simulation experiments are further performed to verify the effectiveness of the proposed control strategy without Zeno phenomenon.