Control Gain Determination Method for Robust Time-Delay Control of Industrial Robot Manipulators Based on an Improved
Yu Chen1, Jianwan Ding1, Tianchang Xu1
1School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
This study introduces a new robust time-delay control for robotic manipulators, enhancing industrial manufacturing. The improved method offers precise trajectory tracking and better noise suppression for reliable state estimation.
Area of Science:
- Robotics
- Control Systems Engineering
- Industrial Automation
Background:
- Robotic manipulators require high-precision control for industrial manufacturing efficiency.
- Nonlinear dynamics, time-varying characteristics, and external noise complicate accurate robotic control and state estimation.
- Conventional time-delay control methods face challenges in computational intensity for gain determination and effective noise suppression.
Purpose of the Study:
- To propose a robust time-delay control strategy for robotic manipulators.
- To develop an improved state observer for accurate state estimation and noise suppression.
- To enhance trajectory tracking accuracy and overall control performance in industrial robotic systems.
Main Methods:
- Derivation of a linearized dynamic model for robotic manipulators.
- Development of an offline computation scheme for simplified control gain determination.
- Integration of model reference estimation with noise suppression techniques in a novel state observer.
Main Results:
- The proposed method efficiently determines control gains without additional tuning parameters.
- The improved state observer accurately acquires joint states, even under noisy conditions.
- Experimental validation demonstrates superior trajectory tracking accuracy and control performance compared to existing methods.
Conclusions:
- The novel time-delay control strategy effectively addresses challenges in robotic manipulator control.
- The integrated state observer significantly improves robustness and state estimation accuracy.
- The developed approach offers a more efficient and effective solution for high-precision industrial robotic applications.
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