Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

In this paper, we propose an approach to tune optimal parameters of a robust PID controller by means of computed torque control (CTC) strategy for trajectory tracking of a Delta parallel robot, using a hybrid optimization algorithm of Particle Swarm Optimization (PSO) and differential evolution (DE)...

Full description

Saved in:
Bibliographic Details
Published in:Robotica 2023-04, Vol.41 (4), p.1159-1178
Main Authors: Pak, Yong-Ju, Kong, Yong-Su, Ri, Jin-Song
Format: Article
Language:English
Subjects:
Algorithms
Attenuation
Closed loop systems
Constraint modelling
Control theory
Controllers
Design specifications
Dynamic models
Evolutionary computation
Global optimization
Kinematics
Nonlinear dynamics
Optimization algorithms
Parameter robustness
Particle swarm optimization
Process controls
Proportional integral derivative
Robots
Robust control
Tracking control
Trajectory control
Tuning
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we propose an approach to tune optimal parameters of a robust PID controller by means of computed torque control (CTC) strategy for trajectory tracking of a Delta parallel robot, using a hybrid optimization algorithm of Particle Swarm Optimization (PSO) and differential evolution (DE). It differs from previous works that they propose robust PID controller parameters tuning based on conventional gradient-based optimization algorithms and apply them to process control. First, we reduce the tuning problem of a robust PID controller with CTC strategy satisfying requirements including robustness and disturbance attenuation to an optimization problem with nonlinear constraints by considering the nonlinear dynamic model of a Delta parallel robot. Second, we set up the design characteristics for the trajectory tracking of a Delta parallel robot. Then, we propose a robust PID controller in a way of obtaining the global optimization solution of the nonlinear optimization problem by running a PSO-DE hybrid optimization algorithm of finding the global optimal solution by maintaining the diversity of swarm during evolution based on the evolution of cognitive experience. Simulation and experimental results demonstrate that the proposed controller outperforms previous works with respect to robust performance and active disturbance attenuation when it is applied to tracking control of a Delta parallel robot.
ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574722001606