Neuroadaptive‐based fixed‐time control for robotic manipulators with uniform prescribed performance under unknown disturbance

Achieving faster convergence, smaller transient overshoots, and higher steady‐state tracking accuracy is essential to improve the efficiency, robustness, and applicability of robotic manipulators. This article introduces an innovative adaptive fixed‐time uniform prescribed performance controller for...

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Veröffentlicht in:	International journal of robust and nonlinear control 2024-10, Vol.34 (15), p.10683-10703
Hauptverfasser:	Liu, Chengguo, Li, Junyang, He, Ye, Jing, Anyan, Li, Longnan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control adaptive neural network barrier Lyapunov function Convergence disturbance observer Disturbance observers Dynamic models Error analysis Error signals fixed‐time control Manipulators Neural networks Parameter modification Parameter uncertainty Performance measurement prescribed performance Robot arms Robot control Robust control Stability analysis
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