Title :
Particle Swarm Optimization for PID Controllers with Robust Testing
Author_Institution :
Lunghwa Univ. of Sci. & Technol., Guishan
Abstract :
In this paper a design method which optimizes PID parameters of motion systems via the particle swarm algorithm (PSO) is presented. Simulations and experiments show that the PID controller via the particle swarm optimization (PSO-PID) performs better time response than the known genetic algorithm method. Through the results, the PSO-PID controller has also been proven to be more efficient than the genetic algorithm in seeking for the global optimum PID parameters with respect to the desired performance indices. In addition, the robust testing for the PID controller via PSO has been presented well.
Keywords :
genetic algorithms; particle swarm optimisation; self-adjusting systems; three-term control; PID controllers; genetic algorithm; motion systems; particle swarm optimization; robust testing; Control systems; Cybernetics; Error correction; Genetic algorithms; Machine learning; Particle swarm optimization; Proportional control; Robust control; Testing; Three-term control; PID controller; PSO-PID; Particle swarm optimization; Robust testing;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0972-3
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370280