Neural Network-Based Optimal Fault-Tolerant Control for Interconnected Nonlinear Systems With Actuator Failures

In this study, we present a decentralized optimal fault-tolerant control (FTC) framework using neural networks (NNs) for interconnected nonlinear systems. This approach addresses challenges arising from unknown drift functions, interconnections, and multiple faults, including lock-in-place, loss of...

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Veröffentlicht in:	IEEE transactions on emerging topics in computational intelligence 2024-04, Vol.8 (2), p.1828-1840
Hauptverfasser:	Wang, Yujia, Wang, Tong, Li, Chuang, Yang, Jiae
Format:	Artikel
Sprache:	eng
Schlagworte:	Actuator failure Actuator faults Actuators Adaptive control Computer simulation Control systems design Dynamic programming Effectiveness Fault tolerance Fault tolerant systems Feedback control Heuristic algorithms Machine learning Neural networks Nonlinear control Nonlinear systems Optimal control Optimal tracking control Parameter estimation Parameter search algorithm Power system dynamics Search algorithms Search methods Steady-state Tracking control
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