基于差分算法的预测控制  

Predictive Control Based on Differential Evolution Algorithm

作　　者：高承武[1] 侯立刚[1] 李会举[1] 苏成利[1] 

机构地区：[1]辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001

出　　处：《辽宁石油化工大学学报》2009年第3期62-64,共3页Journal of Liaoning Petrochemical University

摘　　要：针对参数可变的非线性模型,提出了一种基于差分算法的预测控制。利用神经网络依据系统的输入输出数据建立预测模型,并利用差分算法对其进行滚动优化,从而提高控制系统的性能。最后,分别运用遗传算法和差分算法实现滚动优化进行预测控制仿真,并对两种方法的仿真结果进行比较。仿真结果表明,采用差分进化算法进行滚动优化的预测控制总体效果相对较好。A predictive control method based on differential evolution was put forward in connection with changing parameters nonlinear model By using neural network and accord as input and output data of the system, a predictive model was established. And then differential evolution algorithm was used to do rolling optimization and improve system performance accordingly. At last, GA and DE were used respectively to do predictive simulation to realize the rolling optimization and compare the two results. The two simulation results show that the rolling optimization of predictive control based on DE is better than that based on GA on the whole.

关 键 词：预测控制 神经网络 差分算法 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]