Distributed Estimator-Based Fuzzy Containment Control for Nonlinear Multiagent Systems With Deferred Constraints
Hui Ma, Qi Zhou, Hongru Ren, Zhenyou Wang
Abstract
In this article, we concentrate on the adaptive fuzzy containment control approach for a class of nonlinear multiagent systems with deferred constraint and actuator failure. First, considering that not all agents can directly receive the leader signals, this article constructs a distributed prescribed-time estimator to provide each agent with a corresponding reference signal, thereby the containment problem is constructed as a tracking problem. Subsequently, with the help of the prescribed-time scaling function and the barrier function, the problem of deferred output constraint is reformulated as a boundedness problem of the new variable. By introducing several useful lemmas, the designed controller can ensure that the closed-loop signals are bounded in the presence of actuator fault in the system. In addition, through the designed fuzzy control algorithm, it can strictly guarantee that the system output converges within the ideal range after the settling time. The superiority and effectiveness of this method are verified through robots experiments.