Automated Particle Swarm Optimization Based PID Tuning for Control of Robotic Arm
Ouboti Djaneye-Boundjou, Xingsheng Xu
We revisit the Proportional-Integral-Derivative (PID) controller design for torque control of robotic manipulators, for which, appropriate tuning of the said controller could prove very burdensome, especially with increasing degrees-of-freedom (DOF) and/or when designing a Multi- Input Multi-Output (MIMO) PID controller. That is, when generating and tuning matrix P-I-D gains as opposed to single values, in order to take in account possible coupling effects between involved joints. We tackle both joint space and workspace PID control tuning problems for reference tracking from an optimization standpoint. Using a previously developed stable Adaptive Particle Swarm Optimizer, we are able to automatically and systematically tune P-I-D gains, be it as single gain values or gain matrices, while optimizing a cost or fitness function. The aforesaid cost function can be arranged to feature various aggregated performance measures, ‘normalized’ so as to overcome differences in scale if any. Taking in account some practical limitations, a 2-DOF arm is used here as a case study. Numerical simulations are provided to substantiate the adequacy of our method.
Graduate Research - Graduate
Raul E Ordonez
Primary Advisor's Department
Electrical and Computer Engineering
Stander Symposium poster
"Automated Particle Swarm Optimization Based PID Tuning for Control of Robotic Arm" (2017). Stander Symposium Posters. 1077.