A theoretical control method for a fixed-time all-drive system with state constraints for a robotic arm
By combining nonlinear transformation and fixed-time sliding mode control with radial basis function adaptive law to optimize controller gain, the complexity and constraints of robotic arm joint angle tracking control are solved, achieving fast, stable, and high-precision tracking results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SICHUAN UNIV
- Filing Date
- 2025-09-17
- Publication Date
- 2026-05-26
AI Technical Summary
Existing robotic arm joint angle tracking control methods suffer from design complexity, differential explosion problem, limited convergence performance, difficulty in handling state constraints, and challenges in controller gain tuning, making it difficult to achieve high-precision, fast, and stable tracking control under unmodeled dynamics and external disturbances.
A nonlinear transformation function is used to map joint angle constraints to an unconstrained transformation variable space. A fixed-time controller is designed by combining fixed-time sliding mode control and radial basis function adaptive law. The controller gain is optimized by the optimal control problem, and an all-drive system model is constructed to handle unknown disturbances and constraints.
It achieves rapid convergence within a finite time, online compensation for unmodeled dynamics and external disturbances, simplifies controller design, improves the tracking accuracy and robustness of the robotic arm joint angle, reduces computational complexity, and is suitable for multi-degree-of-freedom robotic arm systems.
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Figure CN121223768B_ABST