摘要
针对矿灯充电系统的多变量、非线性和离散性特点,提出一种基于PSO优化的模糊PID矿灯充电控制策略。基于变论域的思想,采用PSO优化模糊控制器的量化因子参数,将该方法用于矿灯充电控制系统,同时与GA优化算法进行对比。
Considering the miner charging system variables,nonlinear,and discrete features,fuzzy PID optimization based on PSO the miner charging control strategy.Variable Region-based thinking,using the parameters of the PSO optimization of the quantization factor of the fuzzy controller,this method is used to miner's lamp charge control system,compared with GA optimization algorithm.Simulation results show that the convergence rate of the proposed algorithm is fast,ultra-adjust the amount is small.
出处
《重庆科技学院学报（自然科学版）》
CAS
2012年第6期140-142,共3页
Journal of Chongqing University of Science and Technology：Natural Sciences Edition
关键词
充电
模糊PID
粒子群优化
遗传算法
charging
fuzzy PID
particle swarm optimization
genetic algorithm
