Adaptive Interleaved Reinforcement Learning: Robust Stability of Affine Nonlinear Systems With Unknown Uncertainty

This article investigates adaptive robust controller design for discrete-time (DT) affine nonlinear systems using an adaptive dynamic programming. A novel adaptive interleaved reinforcement learning algorithm is developed for finding a robust controller of DT affine nonlinear systems subject to matc...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 33; H. 1; S. 270 - 280
Hauptverfasser:	Li, Jinna, Ding, Jinliang, Chai, Tianyou, Lewis, Frank L., Jagannathan, Sarangapani
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive learning Adaptive systems Algorithms Control systems design Controllers Discrete time systems Dynamic programming Interleaved reinforcement learning Linear systems Machine learning Neural networks neural networks (NNs) Nonlinear systems Optimal control Performance evaluation Reinforcement Robust control Robust stability Stability System effectiveness uncertain systems Uncertainty
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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