Adaptive neural tracking control for non‐affine switched systems with multiple time delays and actuator faults. (20th June 2022)

• Record Type: Journal Article
• Authors: Wu, Yang; Zhang, Guoshan; Wu, Li‐Bing
• Is Part Of: International journal of adaptive control and signal processing. Volume 36:Number 9(2022)
• Page Start: 2289
• Page End: 2304
• Publication Date: 2022-06-20
• Subjects: actuator faults -- adaptive tracking control -- average dwell time -- fault‐tolerant control -- non‐affine switched systems; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3457
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: In this article, an adaptive output feedback neural tracking control algorithm is studied for non‐affine switched systems with multiple time delays and actuator faults. First, an adaptive neural state observer, which only needs to update a parameter online, is presented to estimate the unmeasurable state, and Lipschitz condition is used to deal with delay fault so as to avoid complex delay assumption. Then, by using online estimation information and backstepping technique, a switched fault‐tolerant control mechanism is established for non‐affine switched systems, the designed controller of each subsystems can ensure that non‐affine switched systems output signal can track reference signal under switch signals with average dwell time and all closed‐loop signals are bounded in the presence of multiple time delays, actuator faults, and external disturbances. Finally, simulation results verify the effectiveness of the proposed algorithm.