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...

Celý popis

Podrobná bibliografie

Vydáno v:	Computers & electrical engineering Ročník 116; s. 109179
Hlavní autoři:	Khalili Amirabadi, Roya, Solaymani Fard, Omid
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.05.2024
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!