Reinforcement learning for robust adaptive control of partially unknown nonlinear systems subject to unmatched uncertainties

This paper proposes a novel robust adaptive control strategy for partially unknown continuous-time nonlinear systems subject to unmatched uncertainties. Initially, the robust nonlinear control problem is converted into a nonlinear optimal control problem by constructing an appropriate value function...

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Vydané v:	Information sciences Ročník 463-464; s. 307 - 322
Hlavní autori:	Yang, Xiong, He, Haibo, Wei, Qinglai, Luo, Biao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.10.2018
Predmet:	Adaptive dynamic programming Neural networks Optimal control Reinforcement learning Robust control Unmatched uncertainty Robust control Unmatched uncertainty Adaptive dynamic programming Neural networks Optimal control Reinforcement learning
ISSN:	0020-0255, 1872-6291
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