控制理论(社会学)
PID控制器
机械臂
粒子群优化
运动学
弹道
控制器(灌溉)
计算机科学
非线性系统
运动控制
模糊逻辑
控制工程
机器人
工程类
人工智能
控制(管理)
物理
机器学习
生物
经典力学
量子力学
农学
温度控制
天文
作者
Kun-Jui Wu,Mei-Yung Chen
标识
DOI:10.1109/ifuzzy60076.2023.10324208
摘要
This paper uses the Denavit-Hartenberg (D-H) convention to derive the motion model, including the kinematics and dynamics, of the 6-DOF robotic arm. In order to overcome the highly nonlinear issue of the motion model, we linearize the nonlinear system by T-S fuzzy modeling. Based on the linearized model, we can control the robotic arm through a parallel distributed PID controller. According to the requirements of the continuous trajectory, the length limits of each arm, and the angle limits of the joint rotation, the design of motion form needs to fit the motion model of the robot arm. The parameters of the PID controller are found by the particle swarm optimization (PSO). According to the system transfer function, the controller with the optimized parameters can resist the uncertainty of the system, and make the robot arm move more efficiency and smoothly. The system is simulated in Matlab with Simulink, and its analysis scope includes fixed-point and trajectory tracking. Compared with the traditional PID controller, the results show that the proposed controller has less stability errors, overshoots and vibrations.
科研通智能强力驱动
Strongly Powered by AbleSci AI