TY - GEN
T1 - Controller with the PID Parameters Optimization by PSO for a 6-DOF Robotic Arm
AU - Wu, Kun Jui
AU - Chen, Mei Yung
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
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U2 - 10.1109/iFUZZY60076.2023.10324208
DO - 10.1109/iFUZZY60076.2023.10324208
M3 - Conference contribution
AN - SCOPUS:85179583931
T3 - 2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023
BT - 2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2023
Y2 - 26 October 2023 through 29 October 2023
ER -