Command filter-based adaptive fault-tolerant tracking control for uncertain non-strict feedback multi-agent systems with or without state constraints

Abstract

This paper considers the topic of adaptive leader-following fault-tolerant tracking control for a class of non-strict feedback nonlinear multi-agent systems with or without state constraints in a unified solution. Through the use of certain transformation techniques, the original constraint system is recast as a new completely unconstrained system. Compared with the existing results, the limitation that the constraint functions need upper bound is relaxed. By employing radial basis function neural networks (RBFNNs) to approximate the unknown functions. A novel adaptive fault-tolerant consensus tracking control (CTC) manner is raised with command filtered backstepping design. Then, through the Lyapunov stability analysis, the proposed scheme can ensure all signals in the closed-loop system are cooperative semi-globally uniformly ultimately bounded (SGUUB). Finally, simulation example confirms the efficiency of the proposed method.