Adaptive PID control method for laparoscopic surgical robotic arm
10.3969/j.issn.1005-202X.2025.10.018
- VernacularTitle:腹腔镜手术机械臂自适应PID控制方法
- Author:
Yirong ZHU
1
;
Guanghong TAO
;
Xiaozhen LI
Author Information
1. 安徽科技学院智能制造学院,安徽 滁州 239000
- Publication Type:Journal Article
- Keywords:
laparoscopic surgery;
PID control;
adaptive;
robotic arm
- From:
Chinese Journal of Medical Physics
2025;42(10):1393-1400
- CountryChina
- Language:Chinese
-
Abstract:
Objective To propose an improved scheme based on an adaptive PID control strategy for effectively optimizing the positioning accuracy and reliability of laparoscopic surgical robotic arm during practical operations.Methods The particle swarm optimization algorithm was employed to adjust the proportional(Kp),integral(Ki),and derivative(Kd)parameters of the PID controller in real-time and online.A simulation experimental platform for laparoscopic surgical robotic arm was built based on a multi-degree-of-freedom kinematic model,and verification was conducted through both typical path planning and simulated disturbance tests.High-precision sensors were used to obtain trajectory deviation data,and control experiments were carried out under the traditional PID control mode and the adaptive PID control mode.The root mean square error and response time were compared.Results The average root mean square error of trajectory tracking error and the average response time of the adaptive PID control method were lower or shorter than those of the traditional PID control method(0.853 mm vs 2.665 mm;4.34 s vs 5.64 s).Furthermore,the adaptive PID control effectively suppressed the overshoot and oscillation phenomena commonly seen in traditional PID control,demonstrating more stable and reliable overall performance.Conclusion The proposed scheme addresses the inherent limitations of traditional PID control,improves the operation accuracy and stability of laparoscopic surgical robotic arm in complex dynamic surgical environments,and provides important theoretical foundations and technical support for the design optimization of robot-assisted surgical systems,holding significant clinical application value and social benefits.
