Fault-Tolerant Optimal Control for Discrete-Time Nonlinear System Subjected to Input Saturation: A Dynamic Event-Triggered Approach

Peng Zhang, Yuan Yuan, Lei Guo

Research output: Contribution to journalArticlepeer-review

76 Scopus citations

Abstract

This paper investigates the dynamic event-triggered fault-tolerant optimal control strategy for a class of output feedback nonlinear discrete-time systems subject to actuator faults and input saturations. To save the communication resources between the sensor and the controller, the so-called dynamic event-triggered mechanism is adopted to schedule the measurement signal. A neural network-based observer is first designed to provide both the system states and fault information. Then, with consideration of the actuator saturation phenomenon, the adaptive dynamic programming (ADP) algorithm is designed based on the estimates provided by the observer. To reduce the computational burden, the optimal control strategy is implemented via the single network adaptive critic architecture. The sufficient conditions are provided to guarantee the boundedness of the overall closed-loop systems. Finally, the numerical simulations on a two-link flexible manipulator system are provided to verify the validity of the proposed control strategy.

Original languageEnglish
Article number8752272
Pages (from-to)2956-2968
Number of pages13
JournalIEEE Transactions on Cybernetics
Volume51
Issue number6
DOIs
StatePublished - Jun 2021

Keywords

  • Adaptive dynamic programming (ADP)
  • dynamic event-triggered mechanism (ETM)
  • fault-tolerant control (FTC)
  • input saturation
  • neural network

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