Actuator fault tolerance evaluation approach of nonlinear model predictive control systems using viability theory. (November 2018)

• Record Type: Journal Article
• Authors: Ghaniee Zarch, Majid; Puig, Vicenç; Poshtan, Javad; Shoorehdeli, Mahdi Aliyari
• Is Part Of: Journal of process control. Volume 71(2018)
• Page Start: 35
• Page End: 45
• Publication Date: 2018-11
• Subjects: Fault tolerance evaluation -- Viability theory -- Set invariance theory -- Model predictive control -- Linear parameter varying system; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2018.08.006
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: Propose an approach to evaluate the actuator fault tolerance. A nonlinear model predictive control (NMPC) system is considered. The system is represented in a linear parameter varying (LPV) form. Viability theory concepts in a set form (viability kernel, capture basin) is used. Assess if after the fault the NMPC controller will be able to achieve their goal. An algorithm is developed to assess the tolerance of the NMPC controller. Two application examples (pasteurization plant, mobile robot) are used. Abstract: In this paper, an approach to evaluate the actuator fault tolerance of a nonlinear model predictive control (NMPC) system using viability theory is proposed. Viability theory provides several concepts formulated in a set form (viability kernel and capture basin) that are very useful to assess if after the fault the NMPC controller will be able to achieve their goal either using a reconfiguration or an accommodation strategy. By representing the nonlinear model of the system in a linear parameter varying (LPV) form and using zonotopes to evaluate viability sets, an algorithm is developed and implemented that is able to assess the tolerance of the NMPC controller. To illustrate the proposed approach two application examples based on well-known control problems (a pasteurization plant and a mobile robot) are used.