Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems. (March 2015)

• Record Type: Journal Article
• Authors: Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem
• Is Part Of: ISA transactions. Volume 55(2015:Mar.)
• Page Start: 100
• Page End: 115
• Publication Date: 2015-03
• Subjects: Adaptive control -- Backstepping approach -- Fault tolerant control -- MIMO uncertain nonlinear systems -- Sensor faults; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2014.10.001
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Highlights: An active fault tolerant control scheme is investigated for a class of second-order MIMO uncertain nonlinear systems. An adaptive backstepping controller is developed against time-varying with derivative bounded sensor faults and uncertainties. The proposed AFTC system can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. The fault detection and isolation (FDI) task is not required. The on-line fault estimation and compensation is performed using an adaptive algorithm.