Adaptive nonlinear model predictive control for a class of multivariable chemical processes

YANG Jianfeng; ZHAO Jun; QIAN Jixin; NIU Jian

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Adaptive nonlinear model predictive control for a class of multivariable chemical processes

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- Adaptive nonlinear model predictive control for a class of multivariable chemical processes
- CIESC Journal Issue 4, Pages: 934-940(2008)
- 作者机构：
  
  1. 浙江大学工业控制技术国家重点实验室，工业控制研究所,浙江,杭州,310027
  2. 兰州交通大学自动化与电气工程学院,甘肃,兰州,730070
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：05 April 2008，
  
  Published：05 April 2008
- 稿件说明：
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YANG Jianfeng, ZHAO Jun, QIAN Jixin, et al. Adaptive nonlinear model predictive control for a class of multivariable chemical processes[J]. CIESC Journal, 2008, (4): 934-940.
DOI：

YANG Jianfeng, ZHAO Jun, QIAN Jixin, et al. Adaptive nonlinear model predictive control for a class of multivariable chemical processes[J]. CIESC Journal, 2008, (4): 934-940. DOI：

摘要

针对化工过程的一类多变量非线性系统，提出了一种自适应非线性预测控制(ANMPC)算法。在采用递归最小二乘法进行预测模型参数在线辨识的基础上，将系统的静态非线性关系用一个反向传播(BP)神经网络稳态模型来表示，通过稳态模型求得的动态增益来进一步校正预测模型的参数。详述了ANMPC控制器设计步骤，通过在一个多变量pH中和过程中的仿真验证了本算法的可行性和有效性。

Abstract

An adaptive nonlinear model predictive control (ANMPC) algorithm was proposed for a class of multivariable nonlinear systems in chemical processes.By on-line identifying the parameters of the predictive model with recursive least-squares algorithm

a BP (back propagation) neural network steady-state model was developed to represent the static nonlinearity of the systems

and the parameters of the ARX predictive model were also modulated according to the dynamic gain calculated from the steady-state model.The design procedure of ANMPC controller was elaborated.The simulation results in a multivariable pH neutralization process demonstrated the feasibility and effectiveness of the ANMPC.

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