北京交通大学学报2011，Vol.35Issue(6)：93-97,5.
基于改进遗传算法的单元机组非线性模型参数辨识
Parameters identification of thermal power unit plant nonlinear model based on improved genetic algorithm
任贵杰 1李平康 1赵志刚 2龙俊峰2
作者信息
- 1. 北京交通大学机械与电子控制工程学院,北京100044
- 2. 内蒙古大唐国际托克托第二发电有限责任公司,内蒙占托克托010206
- 折叠
摘要
Abstract
Aiming at characters of the fossil-fired power plant unit and the precocious, and scalability problems of the genetic algorithm toolbox in identifying multivariable nonlinear system parameters, the genetic algorithm toolbox was improved, the nonlinear dynamic model was chosen as the study subject, and the method of parameters identification based on improved genetic algorithm toolbox was proposed. According to the step disturbance test data of 600 MW Unit in Tuoketuo No. 2 Power Plant,the unit model parameters were identified. The results show that the improved genetic algorithm toolbox also has a good adaptability to identify parameters for the unit model,and the identified model is valid and reliable.关键词
单元机组模型/遗传算法/参数辨识Key words
unit plant model/ genetic algorithm/ parameters identification分类
能源科技引用本文复制引用
任贵杰,李平康,赵志刚,龙俊峰..基于改进遗传算法的单元机组非线性模型参数辨识[J].北京交通大学学报,2011,35(6):93-97,5.
