摘要
针对火电厂制粉系统中的钢球磨煤机由于具有纯滞后、大惯性、数学模型难以建立等特点采用数值型模糊控制器,使用伪并行遗传算法对其调整因子、量化殷子和比例因子进行优化,提出了一种适用于多变量对象的适应度函数,同时对交叉和变异算子进行分析和改进,仿真实验结果表明经过优化的模糊控制器具有较好的鲁棒性和抗干扰性。
The ball mill Pulverizing system of power plant is difficult to model mathematically due to time delays and large time constants, so the process is hard to control. Fuzzy control due to its mechanism is fit to control the process whose exact mathematical model is hard to build. However in a fuzzy control system, the performance of fuzz)' controller has a large effect on its control performance, which relies on how to adjust the fuzzy rules. To overcome the difficulties of selection and optimization of fuzzy control rules, a kind of numerical fuzzy controller is designed based on Pseudo-Parallel Genetic Algorithms (PPGA), and an adaptive function fit for multi-variable process is presented and the crossover and mutation operators are analysed and modified. The simulation experiments show good stability and robustness of the optimized fuzzy controller.
出处
《控制工程》
CSCD
2005年第S1期53-55,202,共4页
Control Engineering of China
关键词
模糊控制器
伪并行遗传算法
磨煤机系统
参数优化
解析式规则
fuzzy controller
pseudo-parallel genetic algorithms
ball mill system
optimized parameters
analytical rules
