Controller with the PID Parameters Optimization by PSO for a 6-DOF Robotic Arm

Abstract

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.