Adaptive Prescribed-Time Optimal Control for Flexible-Joint Robots via Reinforcement Learning

This article proposes a prescribed-time fuzzy optimal control approach for flexible-joint (FJ) robot systems utilizing the reinforcement learning (RL) strategy. The uniqueness of this method lies in its ability to ensure optimal tracking performance for n-link flexible joint robots within the prescr...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems Jg. 55; H. 4; S. 2633 - 2643
Hauptverfasser:	Xie, Shiyu, Sun, Wei, Sun, Yougang, Su, Shun-Feng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2025
Schlagworte:	Actor-critic structure Backstepping flexible-joint (FJ) robots fuzzy logic systems (FLSs) MIMO Optimal control Performance analysis prescribed-time optimal control Process control Program processors Reinforcement learning reinforcement learning (RL) Robots
ISSN:	2168-2216, 2168-2232
Online-Zugang:	Volltext
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