A Modified Differential Evolution Algorithm and its Application in Thermal Process Model Identification
The mathematical model of the object in power plant is of extremely significance for the design and analysis of the thermal control system. There are many methods to identify the parameters of the desiring object. In this article, we adopt a modified form of a relatively effective yet simple algorithm called differential evolution algorithm (DE) which is a population based stochastic optimization approach. The differential evolution algorithm uses the difference of randomly sampled pairs of vectors in the population for its mutation operators and is applied mainly in real parameter optimization. Based on analysis of DE searching mechanism, the article proposed the improved differential evolution algorithm with self-adaptive parameters to promote its robust, optima searching capability and speed. In order to prove the effectiveness of the improved differential evolution algorithm, we work out relevant model identifying program on MATLAB and identify the mathematical models. Then we analyze the result using the method of comparing.
Changliang Liu Ming Yu
Department of Automation North China Electric Power University Baoding ,China
国际会议
The 2010 International Conference on Intelligent Systems and Knowledge Engineering(第五届智能系统与知识工程国际会议)
杭州
英文
450-453
2010-11-15（万方平台首次上网日期，不代表论文的发表时间）