Fractional-Order Systems Optimal Control via Actor-Critic Reinforcement Learning and Its Validation for Chaotic MFET

Since the existence of fractional order dynamics, it is difficult to obtain an optimality equation to solve for fractional-order optimal control. In this paper, a fractional Hamilton-Jacobi-Bellman (HJB) equation based on error derivative is proposed, and a corresponding online learning algorithm is...

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Veröffentlicht in:	IEEE transactions on automation science and engineering Jg. 22; S. 1173 - 1182
Hauptverfasser:	Li, Dongdong, Dong, Jiuxiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	adaptive dynamic programming Automation Cost function Costs Fractional-order systems Heuristic algorithms neural networks Nonlinear systems Optimal control reinforcement learning (RL) Trajectory
ISSN:	1545-5955, 1558-3783
Online-Zugang:	Volltext
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