A nonlinear model predictive control scheme for sensor fault tolerance in observation processes. (14th July 2020)

• Record Type: Journal Article
• Authors: Knudsen, Brage R.; Alessandretti, Andrea; Jones, Colin N.; Foss, Bjarne
• Is Part Of: International journal of robust and nonlinear control. Volume 30:Number 14(2020)
• Page Start: 5657
• Page End: 5677
• Publication Date: 2020-07-14
• Subjects: exogenous systems -- fault tolerant control -- nonlinear model predictive control -- nonlinear observability -- observation processes; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.5104
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: This article addresses the problem of designing a sensor fault‐tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider sensor faults captured by a change in a set of sensor parameters affecting the measurements. Using this parametrization, we present a nonlinear model predictive control (NMPC) scheme to control the observation process and actively detect and estimate possible sensor faults, with adaptive controller reconfiguration to optimize the use of the remaining sensing capabilities. A key feature of the proposed scheme is the design of observability indices for the NMPC stage cost to improve the observability of both the state of the exogenous system and the sensor fault parameters. The effectiveness of the proposed scheme is illustrated through numerical simulations.