Trajectory Tracking Control of a Six-Degree-of-Freedom Manipulator Based on EAVOA-LADRC
Year: 2025
Type: article
Abstract: In the trajectory tracking control of the manipulator, since it is difficult to establish an accurate system model for the manipulator, the use of Linear Active Disturbance Rejection Control (LADRC), although it does not rely on an accurate system model, is difficult to obtain the optimal parameters in practical applications, which affects the control accuracy. Therefore, a linear self-imposed perturbation parameter tuning method based on the Enhance African Vulture Optimization Algorithm (EAVOA) is proposed. In order to solve the problem that the AVOA is unbalanced between the exploration stage and the development stage, and is prone to fall into the local optimal solution, the Kent Chaos initialization, Cauchy inverse learning, optimization of the F computation, and introduction of inhibition coefficients are proposed as the improvement strategies. Through experimental comparison, the improved algorithm has faster convergence speed and better optimal solution, and has smaller joint angle error in the trajectory tracking control of six-degree-of-freedom manipulator based on LADRC.
Source: IEEE Access
Authors: Xinxin Shi, Haihao Yu
Institution: Nanjing Institute of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
Award: 具有执行器非线性约束的切换非完整系统的固定时间控制研究
OpenAlex ID: W4412375776
