Robust Adaptive Dynamic Programming and Feedback Stabilization of Nonlinear Systems

This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dy...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 25; H. 5; S. 882 - 893
Hauptverfasser:	Jiang, Yu, Jiang, Zhong-Ping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.05.2014 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptative systems Adaptive dynamic programming (ADP) Applied sciences Approximation methods Artificial intelligence Closed loop systems Computer science; control theory; systems Control system synthesis Control systems Control theory Control theory. Systems Design engineering Dynamic programming Dynamical systems Exact sciences and technology Learning Learning and adaptive systems Nonlinear dynamics Nonlinear systems nonlinear uncertain systems Nonlinearity Optimal control robust optimal control Robustness Uncertainty nonlinear uncertain systems Adaptive dynamic programming (ADP) robust optimal control Methodology Non linear control Feedback regulation Control synthesis Optimization Optimal design Uncertain system Unmodeled dynamics Dynamic programming Learning algorithm Optimal control (mathematics) Single machine Adaptive dynamic programming Turbojet Reinforcement learning Jet engine Non linear system Recursive algorithm Backstepping control Robust control Optimal control Small gain theorem Control theory Artificial intelligence Output feedback Lyapunov function
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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