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

• Published in: IEEE transactions on cybernetics Vol. 51; no. 6; pp. 2956 - 2968
• Main Authors: Zhang, Peng, Yuan, Yuan, Guo, Lei
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Adaptive control; Adaptive dynamic programming (ADP); Algorithms; Discrete time systems; dynamic event-triggered mechanism (ETM); Dynamic programming; Fault tolerance; Fault tolerant systems; fault-tolerant control (FTC); Feedback control; Flexible manipulators; input saturation; neural network; Neural networks; Nonlinear control; Nonlinear dynamical systems; Nonlinear systems; Observers; Optimal control; Output feedback; Saturation; Schedules
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2019.2923011

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.