摘要
为了解决PID控制器参数整定过程中的优化和复杂性问题,增强PID控制器参数整定的自适应性,结合差异演化算法和粒子群算法,提出一种带有差异演化变异算子的粒子群混合优化算法,利用一维云模型映射器将人的控制经验通过语言原子转换为控制规则器,设计具有自适应功能的云模型控制器;将该优化算法应用于一维云模型PID控制器参数整定与优化,并与传统方法进行仿真比较.结果表明,基于带有差异演化变异算子的粒子群混合优化算法的智能控制器具有简单易行、控制性能良好、自适应性和鲁棒性强的特点,可为云模型控制器参数设计提供参考.
In order to effectively solve the optimization,complexity and self-adaptability problems in the parameters optimization design of the PID controller,this paper presents a particle swarm hybrid algorithm with mutation operator of the differential evolution by combining the advantages of the differential evolution and the particle swarm.By using one-dimensional cloud model mapper,human control experience can be converted to the control rulers through language atoms.Then the cloud model with self-adaptability can be designed.The proposed algorithm was applied to the parameters optimization design of the PID controller with one-dimension cloud model,and comparisons were made with the traditional method.Simulation results showed that the hybrid algorithm of the particle swarm with mutation operator of the differential evolution has characteristics of simplicity,better control performance,self-adaptability,and strong robustness for intelligent controller.The proposed method can provide valid theoretical support and application reference for parameters optimization design of the PID controller with cloud model.
出处
《东北石油大学学报》
CAS
北大核心
2013年第4期75-80,92+122-123,共9页
Journal of Northeast Petroleum University
基金
国家自然科学基金青年科学基金项目(61100103)
黑龙江省自然科学基金面上项目(F201219)
关键词
PID控制器
云模型
差异演化
粒子群
混合算法
PID controller
cloud model
differential evolution
particle swarm
hybrid algorithm
