摘要
针对模糊PID控制器参数难以整定的问题,提出一种基于双变异策略协同工作的自适应差分进化算法DSDE。该算法采用随进化代数变化的权重因子,将经由DE/target-to-best/1和DE/rand/2两种变异策略生成的个体加权组合成一个新的变异个体,并采用Z型函数根据迭代次数自动调整变异因子,以适应于不同的进化阶段。将DSDE算法应用于二阶被控对象的模糊PI控制器(FPI)参数整定,MATLAB仿真结果表明,与传统的FPI、DE-FPI和采用自适应变异差分进化算法进行参数整定的AMDE-FPI相比,基于DSDE算法的模糊PI控制器具有更好的控制性能。
To solve the difficulty of parameter tuning for fuzzy PID controller,this paper proposes a self-adaptive differential evolution algorithm with double mutation strategies which is named as DSDE.It employs a weight factor varying with the number of iterations,creates a new individual by weighted combination of two mutated individuals via DE/target-to-best/1 and DE/rand/2 mutation strategies respectively,and uses a Z-type function to automatically adjust the mutation factor to adapt to different stages of evolution.DSDE algorithm is applied to the parameter optimization of a fuzzy PI controller(FPI)for a second-order controlled system.MATLAB simulation results show that DSDE-based fuzzy PI controller(DSDE-FPI)has better control performance than traditional FPI,DE-FPI and AMDE-FPI tuned by adaptive mutation differential evolution algorithm.
作者
陈春霞
孙祥娥
Chen Chunxia;Sun Xiang’e(School of Electronics and Information, Yangtze University, Jingzhou 434024, China)
出处
《武汉科技大学学报》
CAS
北大核心
2020年第3期219-223,共5页
Journal of Wuhan University of Science and Technology
基金
国家重点研发计划项目(2016YFC0303703).
关键词
模糊PI控制器
参数整定
自适应差分进化算法
双变异策略
fuzzy PI controller
parameter tuning
self-adaptive differential evolution algorithm
double mutation strategy
