间歇式反应釜自寻优模糊控制器设计

Design of Self-optimizing Fuzzy Controller for Batch Reactor

以间歇式反应釜温度控制为目标，针对常规模糊控制参数和规则无法在线调整的问题，提出一种基于粒子群算法的自寻优模糊控制器（PSO‐FC），通过引入一个含有加权因子的规则解析式，以时间绝对值误差积分作为系统性能评价函数，利用粒子群算法对加权因子、量化因子等相关参数的取值进行智能寻优，得到一组相对最优的参数，使控制器达到较为理想的控制效果。仿真结果表明，设计的基于粒子群算法的自寻优模糊控制器具有调节精度高、过渡时间短、实时性强等特点，有较高的实用价值。

For the problem that conventional fuzzy control parameters and rules cannot be adjusted online ,a self‐optimizing fuzzy controller based on particle swarm optimization （PSO‐FC） was proposed by taking the batch reactor temperature control as the target .Rule analysis formula including weighting factor was introduced and time absolute value error integral served as system performance evaluation function . Particle swarm optimization was used for intelligent optimizing for the values of weighting factor , weighting factor and relevant parameters to gain a group of relatively optimal parameters . Thus , the controller reached ideal control effect .The simulation result shows that PSO‐FC has such features as high regulation precision ,short transient time and strong instantaneity ,and ow ns high practical value .