Combining hybrid metaheuristic algorithms and reinforcement learning to improve the optimal control of nonlinear continuous-time systems with input constraints

This paper proposes an innovative method for achieving optimal tracking control in nonlinear continuous-time systems with input constraints. The method combines reinforcement learning and hybrid metaheuristics to enhance the controller’s performance. Specifically, a hybrid metaheuristic algorithm is...

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Veröffentlicht in:	Computers & electrical engineering Jg. 116; S. 109179
Hauptverfasser:	Khalili Amirabadi, Roya, Solaymani Fard, Omid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.05.2024
Schlagworte:	Actor-critic neural network Hybrid metaheuristic algorithms Nonlinear systems Optimal tracking control Reinforcement learning Hybrid metaheuristic algorithms Optimal tracking control Nonlinear systems Actor-critic neural network Reinforcement learning
ISSN:	0045-7906, 1879-0755
Online-Zugang:	Volltext
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