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Fault tolerant tracking control for a class of linear parameter varying systems using reduced-order simultaneous estimator and optimal preview policy

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  • Kezhen Han
  • Jian Feng

Abstract

This paper considers the reduced-order estimator based fault tolerant preview tracking control problem for a class of linear parameter varying (LPV) systems. The main research contents are composed of two aspects. First, a scheduling-parameter-dependent reduced-order simultaneous state/fault estimator is designed based on model transformation method, unknown input observer theory, estimator parameterisation, and robustness optimisation. Second, a novel robust fault tolerant preview tracking control policy is constructed by integrating fault signal compensation, state feedback, preview action of reference signals, and integral regulation of tracking errors. Compared with the relevant studies, the merits can be summarised in two aspects. On one hand, the proposed design method of reduced-order estimator can be applied to more general LPV models because it does not depend on the traditional constraint operations, such as decomposition of system output equation, separated estimations of actuator and sensor faults, or derivative of output equation. On the other hand, the optimal preview policy including preview action and integral regulation is introduced to increase the design degree of freedom, which contributes to the optimisation of fault tolerant tracking performance even under influences of fault estimation errors and disturbances. Finally, the effectiveness of the proposed method is verified by three case studies.

Suggested Citation

  • Kezhen Han & Jian Feng, 2020. "Fault tolerant tracking control for a class of linear parameter varying systems using reduced-order simultaneous estimator and optimal preview policy," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(2), pages 313-333, January.
  • Handle: RePEc:taf:tsysxx:v:51:y:2020:i:2:p:313-333
    DOI: 10.1080/00207721.2019.1704096
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