摘要
PID控制在工业生产中得到广泛的应用,其性能指标取决于PID参数的选取。粒子群算法是一种常见的智能化算法,简单便于实现,文章采取基于自然选择改进的粒子群算法优化PID控制器的参数,与经典的粒子群算法相比较,文章所提出的算法有效地避免了经典粒子群算法过早陷入局部最优的问题,具有较高的求解效率。
PID control has been widely employed in industrial production, and the performance of PID control depends on the selection of PID parameters. Particle swarm optimization is one of the most popular intelligent algorithms for the sake of easy to implement. In this paper, particle swarm optimization based on Natural Selection is used to optimize the parameters of the PID controller. Compared with the classical particle swarm optimization, the algorithm proposed in this paper effectively avoids getting in the local best solution and has higher efficiency.
出处
《大众科技》
2019年第3期1-3,共3页
Popular Science & Technology
基金
桂林理工大学科研启动基金资助项目(GLUTQD2018001)
关键词
自然选择
粒子群算法
PID控制器
natural selection
particle swarm optimization
PID controller
