Adaptive sensor fault-tolerant control for a class of multi-input multi-output nonlinear systems: Adaptive first-order filter-based dynamic surface control approach. (September 2018)

• Record Type: Journal Article
• Authors: Khebbache, Hicham; Labiod, Salim; Tadjine, Mohamed
• Is Part Of: ISA transactions. Volume 80(2018)
• Page Start: 89
• Page End: 98
• Publication Date: 2018-09
• Subjects: Adaptive control -- Adaptive first-order filter -- Dynamic surface control (DSC) -- Fault-tolerant control (FTC) -- Robust and fast estimation -- Sensor fault; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2018.07.037
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper is concerned with the adaptive fault-tolerant control (FTC) problem for a class of multivariable nonlinear systems with external disturbances, modeling errors and time-varying sensor faults. The bias, drift, loss of accuracy and loss of effectiveness faults can be effectively accommodated by this scheme. The dynamic surface control (DSC) technique and adaptive first-order filters are brought together to design an adaptive FTC scheme which can reduce significantly the computational burden and improve further the control performance. The adaptation laws are constructed using novel low-pass filter based modification terms which enable under high learning or modification gains to achieve robust, fast and high-accuracy estimation without incurring undesired high-frequency oscillations. It is proved that all signals in the closed-loop system are uniformly ultimately bounded and the tracking-errors can be made arbitrary close to zero. Simulation results are provided to verify the effectiveness and superiority of the proposed FTC method. Highlights: The FTC problem is investigated for a class of n -th order multivariable nonlinear systems with time-varying sensor faults. The proposed FTC scheme can effectively accommodate four kinds of sensor faults. The proposed method is developed by incorporating adaptive first-order filters into the dynamic surface control framework. No prior knowledge about the upper-bounds of the derivatives of virtual controls is needed in the design. The online estimation schemes are designed by introducing novel low-pass filter-based modification terms.