Adaptive Fuzzy-Based Fault-Tolerant Boundary Control of Flexible Timoshenko Manipulators Under Directed Graph
Xiangqian Yao, Wei Zhao, Yu Liu
Abstract
This article investigates distributed adaptive fuzzy-based boundary vibration control and cooperative tracking for a directed flexible Timoshenko manipulator network with process and actuator faults, disturbances, and modeling uncertainties. In control design, fuzzy logic systems are adopted to estimate the process fault functions, and the adaptive method is used to compensate for the effects of actuator gain failures, disturbances, and modeling uncertainties. Then, by utilizing a combination of boundary consensus control, integral control, and adaptive fuzzy control, some novel distributed fault-tolerant controllers are provided to ensure the asymptotic convergence of vibration states and consensus tracking errors in the infinite-dimensional system. Different from the existing results, we prove the asymptotic convergence results directly from the perspective of definition based on some new analytical techniques. At last, some numerical simulation results are presented to illustrate the feasibility of the proposed control algorithms.