Fast Genetic Algorithms Used for PID Parameter Optimization
PID parameter optimization is an important problem in control field. This paper presents a kind of fast genetic algorithms, which have a lot of improvements about population, selection, crossover and mutation in comparison with simple genetic algorithms. These fast genetic algorithms are used in PID parameter optimization for common objective model to remedy flaws of simple genetic algorithms and accelerate the convergence. The algorithms are simulated with MATLAB programming. The simulation result shows that the PID controller with fast genetic algorithms has a fast convergence rate and a better dynamic performance.
Genetic Algorithms Fast Genetic Algorithms Parameter Optimization PID Parameter Tuning
Xiangzhong Meng Baoye Song
Department of Computer Science & Engineering Tongji University Shanghai 200092, China;Automation & E Automation & Electronic Engineering College Qingdao University of Science & Technology Qingdao 26604
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）