摘要
针对传统的模型预测控制不能很好解决具有严重非线性、不确定性的对象或过程的控制问题,提出将模糊模型用于描述对象的非线性动态特性,通过将模糊模型的输出反馈作为模型输入,从而构成了模糊多步预测器。采用一种收敛精度高、速度快的具有最优保留特性遗传算法(EGA),依据模型预测输出在线滚动求解控制律的非线性预测控制算法。仿真结果表明该算法对一类非线性系统具有较快的响应速度和较强的抗干扰能力。
A nonlinear predictive controller based on elitist preserved genetic algorithm(EGA) is presented .Fuzzy model is used to approximate the dynamic of nonlinear processes .By feeding the output of the fuzzy model as the model input in a cascade way ,a multi-step fuzzy predictor is derived.Using this fuzzy model as multi-step predictive model ,we applied EGA to performing the online nonlinear optimization.Simulation results show that the controller has enhanced respones speed and robustness.It is an effective control algorithm combined EGA with predictive control.
出处
《计算机仿真》
CSCD
2004年第12期149-151,共3页
Computer Simulation
关键词
遗传算法
模糊控制
预测控制
Genetic algorithm
Fuzzy control
Predictive control
