首页> 外文会议>International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)论文集 >Nonlinear modeling of drum–boiler–turbine unit using an evolving Takagi–Sugeno fuzzy model
【24h】

Nonlinear modeling of drum–boiler–turbine unit using an evolving Takagi–Sugeno fuzzy model

机译:使用不断发展的Takagi-Sugeno模糊模型对鼓-锅炉-涡轮单元进行非线性建模

获取原文

摘要

The boiler–turbine unit (BTU) is a highly non-linear,multivariable,and time-varying system.The normal linear or quasi-linear modeling can not reflects the real nonlinear characteristics of the BTU,degrading control precision and operating performance.This paper deals with nonlinear modeling of a drum-type BTU using an evolving Takagi–Sugeno (T–S) fuzzy model.A novel method based on fuzzy clustering,least-squares,and genetic algorithms (GA) is proposed to construct a "parsimonious" dynamic T–S fuzzy model with high generalization ability.In this method,a self-organizing fuzzy model generation strategy based on GA is proposed for selecting the optimal structure (including the number of rules and input variables) and antecedent parameters of the fuzzy model.Furthermore,the modified Akaike information criterion is introduced as the evaluation function of GA,which enables the self-organizing strategy to choose an optimal fuzzy model with a good tradeoff between fitting the training data and keeping the model simple.The simulation results show that the developed dynamic T–S fuzzy model can accurately approximates the global behavior of the nonlinear physical model with a low number of rules and fewer input variables.Further,based on the obtained T–S fuzzy model,valid control strategy studies such as predictive control can be developed.
机译:锅炉-涡轮机组(BTU)是一个高度非线性,多变量,时变的系统。正常的线性或准线性建模无法反映BTU的真实非线性特性,从而降低了控制精度和运行性能。本文利用发展中的Takagi-Sugeno(TS)模糊模型对鼓式BTU进行非线性建模。提出了一种基于模糊聚类,最小二乘和遗传算法(GA)的新方法来构造“简约具有高泛化能力的动态TS模糊模型。在这种方法中,提出了一种基于遗传算法的自组织模糊模型生成策略,用于选择模糊结构的最优结构(包括规则数量和输入变量)和先行参数。此外,引入了改进的Akaike信息准则作为GA的评估函数,使自组织策略能够选择最佳的模糊模型,并在拟合训练数据和优化训练数据之间进行权衡取舍。仿真结果表明,所建立的动态TS模糊模型能够以较少的规则和较少的输入变量准确地逼近非线性物理模型的全局行为。该模型可以开发有效的控制策略研究,例如预测控制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号