基于模糊T-S模型的批过程建模与最优控制  

Modeling and Optimal Control of Batch Processes Based on Fuzzy T-S Model

作　　者：张立权[1] 邵诚[1] 

机构地区：[1]大连理工大学信息与控制研究中心,辽宁大连116024

出　　处：《信息与控制》2007年第1期21-28,共8页Information and Control

基　　金：国家科技攻关计划资助项目(2001BA204B01);教育部骨干教师计划资助项目(69825106)

摘　　要：基于模糊T-S模型,提出一种具有自学习能力的模糊方法用于批过程建模和最优控制.通过引入与均方误差相关的动态误差传递因子,使用改进的梯度下降法,本方法能够辨识模糊T-S预测模型.对于批过程的受限非线性最优控制,基于所辨识的预测模型,运用庞特里亚金最小值原理和平行分布补偿算法,本方法能够把一个复杂非线性系统最优控制设计问题转化为一些基于复杂T-S预测模型的局部线性系统的最优问题,从而给出一种有效和简单的模糊最优控制策略.所提方法用于一个半连续式反应器的建模和最优控制,仿真结果表明新方法是有效和准确的.Based on fuzzy T-S model, a fuzzy method with self-learning capability for batch process modeling and optimal control is presented. By introducing the dynamic error transfer factor associated with mean squared error and using the improved gradient descent approach, the proposed method can identify the fuzzy T-S prediction model. For constrained nonlinear optimal control of batch process, with the help of Pomryagin＇s minimum principle （PMP） and parallel distributed compensation algorithm （PDC）, this method can transform the optimal control problem of a complex nonlinear system into the optimal problem of several local linear systems based on fuzzy T-S prediction model. Thus an effective and simple fuzzy optimal control strategy is offered. The presented method has been applied to the modeling and optimal control of a semi-continuous reactor, and simulation results show that this new method is effective and accurate.

关 键 词：批过程 模糊T—S模型 梯度下降法 最优控制 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]