This paper addresses the problem of observer-based fault reconstruction and accommodation for polytopic linear parameter-varying (LPV) systems. A polytopic representation of an LPV system subject to actuator faults and external disturbances is first established; then, a novel polytopic learning unknown-input observer (LUIO) is constructed for simultaneous state estimation and robust fault reconstruction. The stability of the presented LUIO is proved using Lyapunov stability theory together with H∞ techniques. Further, using reconstructed fault information, a reconfigurable fault-tolerant controller is designed to compensate for the influence of actuator faults by stabilizing the closed-loop system. At last, an aircraft example is employed to illustrate the effectiveness and practicability of the proposed techniques.
Fault Reconstruction and Accommodation in Linear Parameter-Varying Systems via Learning Unknown-Input Observers
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 24, 2014; final manuscript received November 7, 2014; published online January 27, 2015. Assoc. Editor: Prashant Mehta.
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Jia, Q., Chen, W., Zhang, Y., and Chen, X. (June 1, 2015). "Fault Reconstruction and Accommodation in Linear Parameter-Varying Systems via Learning Unknown-Input Observers." ASME. J. Dyn. Sys., Meas., Control. June 2015; 137(6): 061008. https://doi.org/10.1115/1.4029250
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