Leader–follower consensus control with hierarchical prescribed performance for nonlinear multi-agent systems under reversing actuator faults

This paper explores the distributed tracking control problem for networked multi-input multi-output (MIMO) strict-feedback nonlinear systems under the influence of unpredictable reversed control direction faults. Based on an intentionally imposed and more lenient controllability condition, we establish a novel hierarchical prescribed performance control (PPC) design framework, comprising two layers: (1) a first-order reference estimator design layer that addresses the distributed control problem by generating the reference signal for each agent; and (2) a reference tracking controller design layer that tracks the reference signals produced by the estimator. Both designs are implemented within a low complexity prescribed performance architecture, thereby enhancing the design flexibility and practical applicability. Notably, several Nussbaum functions are introduced into the reference tracking controller design and a novel recursive method is employed to tackle the challenges posed by reversing faults in stability analysis. Additionally, all closed-loop signals are proven to be globally uniformly ultimately bounded (GUUB). A simulation study demonstrates the efficacy of this method.