THE ADAPTIVE NICHE GENETIC ALGORITHM FOR OPTIMUM DESIGN OF PID CONTROLLER

摘要：

Standard genetic algorithms have the defects of pre-maturity and stagnation when applied in optimizing problems.In order to avoid the shortcomings, an adaptive niche genetic algorithm (ANGA) is proposed.The Elitist strategy is utilized to ensure the stable convergence, niche ideology is used to maintain diversity of evolution population, and the adaptive crossover rate and mutation probability are introduced to enhance the local search ability around every peak value.This algorithm is applied to design of optimal parameters of PID controllers with examples, and the simulation results show that fast tuning of optimum PID controller parameters yields high-quality solution.Compared with the standard genetic algorithm, ANGA is indeed more efficient in improving searching capability and convergence characteristic.

关键词： Elitist strategy Genetic algorithm Convergence Crossover Mutation PID controller

作者: HONG-YAN LI

作者单位: Department of Computer and Electronic Science, Hubei University of Economics, Wuhan 430205, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 487-491

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）