CQPSO Algorithm Based Control System Parameter Optimization

Authors

Genyuan Wei, Hebei Engineering Research Center of Simulation Optimized Control for Power Generation,North China Electric Power University, Baoding 071003, China;
Xinqiang Feng, Hebei Engineering Research Center of Simulation Optimized Control for Power Generation,North China Electric Power University, Baoding 071003, China;
Han Pu, Hebei Engineering Research Center of Simulation Optimized Control for Power Generation,North China Electric Power University, Baoding 071003, China;

Abstract

Abstract: According to the shortcomings of optimization methods of control system parameters, and the result of PSO algorithm usually falling into the partial optimum, Chaos Search and Quantum Space Search were added to the PSO algorithm, constituting the Chaos Quantum Particle Swarm Optimization algorithm, which was applied to the typical thermal control system parameters optimization. Introducing the selection of object functions of control system parameter optimization, describing the CQPSO algorithm process, the CQPSO algorithm was tested and analyzed through multiple test functions. The result shows that, compared with PSO and CPSO algorithm, CQPSO algorithm makes the particle swarm get out of the partial optimization quickly, and improves the accuracy and speed of search. Eventually, the CQPSO algorithm is applied to the PID controller parameters optimization of main steam temperature control system, which offers a credible reference for tuning control parameters and is of great significance.

Recommended Citation

Wei, Genyuan; Feng, Xinqiang; and Pu, Han (2020) "CQPSO Algorithm Based Control System Parameter Optimization," Journal of System Simulation: Vol. 27: Iss. 7, Article 23.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss7/23

First Page

1570

Revised Date

2015-04-06

DOI Link

https://doi.org/

Last Page

1576

CLC

TP18

Recommended Citation

Wei Genyuan, Feng Xinqiang, Han Pu. CQPSO Algorithm Based Control System Parameter Optimization[J]. Journal of System Simulation, 2015, 27(7): 1570-1576.