Adaptive fault-tolerant fuzzy control of robotic systems

Abstract

This paper presents an integrated fault diagnosis and fault-tolerant control methodology for a two-link planar nonlinear robotic systems. Based on the information obtained during a fault diagnostic procedure, a fault-tolerant control component is designed to compensate for the effect of faults using an adaptive learning structure in the form of Takagi-Sugeno fuzzy systems. First, a baseline controller is designed to guarantee the closed-loop system stability in the absence of a fault. Then, a fault-tolerant controller is designed to compensate for the effect of the fault, which is used after fault detection. Under certain assumptions, the stability and tracking performances of the closed-loop system are rigorously investigated. It is shown that the system signals always remain bounded, and the output tracking error converges to a neighborhood of the origin of the state space.