Special Issue: ICCAS 2024

International Journal of Control, Automation, and Systems 2025; 23(2): 520-529

https://doi.org/10.1007/s12555-024-0553-5

© The International Journal of Control, Automation, and Systems

Robust Fault-tolerant Tracking Control for Linear Discrete-time Systems via Reinforcement Learning Method

Ngoc Hoai An Nguyen and Sung Hyun Kim*

University of Ulsan

Abstract

Concentrated on the off-policy reinforcement learning method, this paper explores a model-free algorithm for addressing the robust fault-tolerant tracking problem in discrete-time linear systems with time-varying actuator faults and model uncertainties. Specifically, to determine the feedback control input, a dynamic optimization approach is developed based on measured data rather than exact information from system dynamics. Subsequently, a static optimization approach is established using solutions from the preceding dynamic optimization problem to compute the feedforward control input. Finally, numerical simulations are conducted to illustrate the feasibility and efficiency of the proposed solution.

Keywords Actuator faults, fault-tolerant control, model uncertainties, off-policy approach, reinforcement learning method, robust control, tracking control.

Article

Special Issue: ICCAS 2024

International Journal of Control, Automation, and Systems 2025; 23(2): 520-529

Published online February 1, 2025 https://doi.org/10.1007/s12555-024-0553-5

Copyright © The International Journal of Control, Automation, and Systems.

Robust Fault-tolerant Tracking Control for Linear Discrete-time Systems via Reinforcement Learning Method

Ngoc Hoai An Nguyen and Sung Hyun Kim*

University of Ulsan

Abstract

Concentrated on the off-policy reinforcement learning method, this paper explores a model-free algorithm for addressing the robust fault-tolerant tracking problem in discrete-time linear systems with time-varying actuator faults and model uncertainties. Specifically, to determine the feedback control input, a dynamic optimization approach is developed based on measured data rather than exact information from system dynamics. Subsequently, a static optimization approach is established using solutions from the preceding dynamic optimization problem to compute the feedforward control input. Finally, numerical simulations are conducted to illustrate the feasibility and efficiency of the proposed solution.

Keywords: Actuator faults, fault-tolerant control, model uncertainties, off-policy approach, reinforcement learning method, robust control, tracking control.

IJCAS
February 2025

Vol. 23, No. 2, pp. 359~682

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