Application of a Modified PSO Algorithm in PID Controller Optimization

A modified PSO for Optimum Design of PID Controller is stated. Particle Swarm Optimization is a new random global optimization algorithm. The algorithm feature is simple, ease to implement and powerful function. But it is easy to trap in the local pole, and search accuracy is low. PID controller principle is concise, physical meaning of its parameters are clear, and theoretical analysis system is integrity and the industrial sector are familiar with it, so in the industrial process control is still widely used. In this paper, the modified PSO algorithm has been used in PID controller to optimize parameters and compared with basic PSO algorithm. Emulation experiments demonstrated that the modified PSO algorithm increase the probability convergence to the global optimal solution.

[1]  Wenbo Xu,et al.  Solving Multi-period Financial Planning Problem Via Quantum-Behaved Particle Swarm Algorithm , 2006, ICIC.

[2]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[3]  Nobuyuki Matsui,et al.  Optimal design of robust vibration suppression controller using genetic algorithms , 2002, 7th International Workshop on Advanced Motion Control. Proceedings (Cat. No.02TH8623).

[4]  Jun Zhao,et al.  Application of Particle Swarm Optimization Algorithm on Robust PID Controller Tuning , 2005, ICNC.

[5]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[6]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7]  Ioan Cristian Trelea,et al.  The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..

[8]  Nobuyuki Matsui,et al.  Optimal design of robust vibration suppression controller using genetic algorithms , 2004, IEEE Transactions on Industrial Electronics.

[9]  S. Galvani,et al.  A particle swarm optimization approach for optimum design of PID controller in linear elevator , 2010, 2010 Conference Proceedings IPEC.

[10]  Huang Yourui Application of a modified PSO algorithm in PID parameters optimization , 2008 .