引用本文:刘士荣, 林卫星, 俞金寿, 杨先一.非线性动态系统神经模糊建模与内模/PID双重控制系统设计[J].控制理论与应用,2004,21(4):553~560.[点击复制]
LIU Shi-rong, LIN Wei-xing, YU Jin-shou, Simon X.YANG.Neurofuzzy modeling for nonlinear dynamic systems anddouble control system design with internal model control and PID control[J].Control Theory and Technology,2004,21(4):553~560.[点击复制]
非线性动态系统神经模糊建模与内模/PID双重控制系统设计
Neurofuzzy modeling for nonlinear dynamic systems anddouble control system design with internal model control and PID control
摘要点击 1291  全文点击 1333  投稿时间：2002-03-08  修订日期：2003-06-05
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  
  2004,21(4):553-560
中文关键词  神经模糊系统  内模控制  PID控制  化学反应器
英文关键词  neurofuzzy systems  internal model control  PID control  chemical reactor
基金项目  
作者单位E-mail
刘士荣, 林卫星, 俞金寿, 杨先一 宁波大学 电气工程与自动化研究所,浙江宁波 315211
华东理工大学 自动化研究所,上海 200237
圭尔夫大学 工程系,加拿大 		liusr@mail.nbptt.zj.cn;shliu@uoguelph.ca 
中文摘要
      非线性动态系统的内模控制要求建立精确的对象正模型和逆模型,这对于大多数实际对象是难以做到.提出了基于一类神经模糊模型的非线性动态系统建模方法,并在此基础上研究了基于神经模糊模型的非线性系统的内模控制设计.基于输入输出数据辨识的对象正模型和逆模型存在着模型失配问题,导致神经模糊内模控制范围变窄和控制鲁棒性降低,为了改善系统的性能,提出了神经模糊内模控制与PID控制结合的双重控制策略.对CSTR的反应物浓度控制研究表明,双重控制策略能有效地拓宽系统可控范围,改善系统性能.仿真结果证明该控制策略简单而有效.
英文摘要
      In the internal model control design for nonlinear systems,the precise forward and inverse models of plant are required,but it is impossible in the majority of practical plants.A modeling technique based on a class of neurofuzzy models for nonlinear dynamic systems is proposed.The internal model control design based on neurofuzzy modeling is studied.Because there is the model mismatch problem between the identified forward and inverse models of the plant based on the input_output data of plant,it will make the system controllable range narrowed and the system robustness lessened in the control system based on neurofuzzy modeling.To improve the performance of the control system,the double control strategy with neurofuzzy modeling based internal model control and PID control is proposed.By the concentration control of the reacted mass in a continuous stirred tank reactor (CSTR),the double control strategy is able to effectively extend the system controllable range and improve the performance of the system.The simulation results show that the proposed control strategy is simple and effective.