Prescribed Performance Fault-Tolerant Control of Nonlinear Systems via Actuator Switching

Abstract

This article investigates a prescribed performance control (PPC) problem of nonlinear strict-feedback systems subject to actuator faults. By introducing $ln$ -type performance functions, a constraint of output tracking error is established to prescribe the performance. Via the use of mapping and barrier error transformations, the constraint-handling issue is converted into a stabilization one of unconstrained variable. Then, an adaptive controller involving a fuzzy logic system to approximate the unknown nonlinearity is devised to stabilize the transformed variable, resulting to a universal PPC algorithm that applies to all types of asymmetric prescribed performance requirements. To prevent such requirements from being violated due to actuator faults, a novel dynamic redundancy mechanism is incorporated to implement the performance monitoring and switching from the faulty actuator to a healthy one. Two simulation examples are presented to verify the effectiveness and superiority of the proposed scheme.