Nonlinear adaptive decoupling control for the forced-circulation evaporation process
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- 英文论文题名：Nonlinear adaptive decoupling control for the forced-circulation evaporation process
- 论文作者：Yonggang Wang ; Yu bai ; Nannan Zhang ; Jun Fu ; Tianyou Chai ; Zailin Piao
- 英文论文作者：Yonggang Wang ; Yu bai ; Nannan Zhang ; Jun Fu ; Tianyou Chai ; Zailin Piao ; College of Information and Electronic Engineering ; Shenyang Agricultural University ; State Key Laboratory of Synthetical Automation for Process Industries ; Northeastern University ; IEEE
- 年：2017
- 作者机构：College of Information and Electronic Engineering,Shenyang Agricultural University;State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University;IEEE;
- 英文论文关键词：Forced-circulation evaporator ; Nonlinear decoupling control ; GLC ; Parameter estimation ; EKF
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（A）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
- 语种：英文
- 分类号：TP273;TS205
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：234k
- 原文格式：D
- 会议级别：全国
摘要
The forced-circulation evaporator is a multi-input multi-output nonlinear process which has complex dynamics characteristics, such as strong coupling, serious nonlinearity and parameter uncertainty. As a result, the conventional control strategy can not achieve satisfactory control performance. A nonlinear adaptive decoupling control strategy is proposed in this paper. The control strategy combines globally linearizing control(GLC) algorithm with a parameter estimator. The GLC is used to eliminate the coupling between the two control loops and reduce the effects of the nonlinearities on the system simultaneity. The model parameter is estimated by using an extended Kalman filter(EKF) algorithm, which is able to track changes of the forced-circulation process. Simulation results show that the proposed method has good estimation for the model parameter in addition to the high-quality decoupling control performance provided by the GLC controller.
The forced-circulation evaporator is a multi-input multi-output nonlinear process which has complex dynamics characteristics, such as strong coupling, serious nonlinearity and parameter uncertainty. As a result, the conventional control strategy can not achieve satisfactory control performance. A nonlinear adaptive decoupling control strategy is proposed in this paper. The control strategy combines globally linearizing control(GLC) algorithm with a parameter estimator. The GLC is used to eliminate the coupling between the two control loops and reduce the effects of the nonlinearities on the system simultaneity. The model parameter is estimated by using an extended Kalman filter(EKF) algorithm, which is able to track changes of the forced-circulation process. Simulation results show that the proposed method has good estimation for the model parameter in addition to the high-quality decoupling control performance provided by the GLC controller.
The forced-circulation evaporator is a multi-input multi-output nonlinear process which has complex dynamics characteristics, such as strong coupling, serious nonlinearity and parameter uncertainty. As a result, the conventional control strategy can not achieve satisfactory control performance. A nonlinear adaptive decoupling control strategy is proposed in this paper. The control strategy combines globally linearizing control(GLC) algorithm with a parameter estimator. The GLC is used to eliminate the coupling between the two control loops and reduce the effects of the nonlinearities on the system simultaneity. The model parameter is estimated by using an extended Kalman filter(EKF) algorithm, which is able to track changes of the forced-circulation process. Simulation results show that the proposed method has good estimation for the model parameter in addition to the high-quality decoupling control performance provided by the GLC controller.
引文
[1]Quaak,P.,Van Wijck,M.P.C.,&Van Haren,J.J.Comparison of process identification and physical modeling for falling-film evaporators,Food Control,5(2),73–82,1994.
[2]Tonelli,S.M.,Romagnoli,J.A.,&Porras,J.A.Computer package for transient analysis of industrial multiple-effect evaporators.Journal of Food Engineering,12(4),267–281,1990.
[3]Runyon,C.H.,Rumsey,T.R.,&Mc Carthy,K.L.Dynamic simulation of a nonlinear model of a double effect evaporator.Journal of Food Engineering,14(3),185–201,1991.
[4]Lozano,J.E.,Elustondo,M.P.,&Romagnoli,J.A.Control studies in an industrial apple juice evaporator.Journal of food science,49,1422–1427.1984.
[5]Quaak,P.,Van Wijck,M.P.C.,&Van Haren,J.J.Comparison of process identification and physical modeling for falling-film evaporators,Food Control,5(2),73–82,1994.
[6]Bakker,Huub H.C.,Clive,Marsh,Shabeshe,Paramalingam,&Hong,Chen Cascade controller design for concentration control in a falling-film evaporator,Food Control,17,325–330,2006.
[7]Karimi M.,Jahanmiri A.,&Azarmi M.Inferential cascade control of multi-effect falling-film evaporator,Food control,18,1036-1042,2007.
[8]Kam K.M.,&Tade M.O..Simulated Nonlinear control studies of five-effect evaporator models,Computer and Chemical Engineering,23,(11-12),1795-1810,2000.
[9]To L.C.,TadéM.O.,&Le G.P.Implementation of a differential geometric nonlinear controller on an industrial evaporator system,Control Engineering Practice,6(11),1309-1319,1998.
[10]Lahtinen S.T.Identification of fuzzy controller for use with a falling-film evaporator,Food Control,12,3,175-180,2001.
[11]Rangaiah G.P.Nonlinear model predictive control of an industrial four-stage evaporator system via simulation,Chemical Engineering Computer Journal,87(3),285-299,2002.
[12]Wang Y.G.,Chai T.Y.,Fu J.,&sun J.(2011).Multiple models adaptive cascade decoupling control for the forced-circulation evaporation system,American Control Conference,5061-5066,2001.
[13]Gelb A.Applied Optimal Estimation,MIT Press,MA,1974.
[14]Boutayeb M.,Rafaralahy H.,&Darouach M.Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems,IEEE Trans.Automat.Control,42,581–586,1974.
[2]Tonelli,S.M.,Romagnoli,J.A.,&Porras,J.A.Computer package for transient analysis of industrial multiple-effect evaporators.Journal of Food Engineering,12(4),267–281,1990.
[3]Runyon,C.H.,Rumsey,T.R.,&Mc Carthy,K.L.Dynamic simulation of a nonlinear model of a double effect evaporator.Journal of Food Engineering,14(3),185–201,1991.
[4]Lozano,J.E.,Elustondo,M.P.,&Romagnoli,J.A.Control studies in an industrial apple juice evaporator.Journal of food science,49,1422–1427.1984.
[5]Quaak,P.,Van Wijck,M.P.C.,&Van Haren,J.J.Comparison of process identification and physical modeling for falling-film evaporators,Food Control,5(2),73–82,1994.
[6]Bakker,Huub H.C.,Clive,Marsh,Shabeshe,Paramalingam,&Hong,Chen Cascade controller design for concentration control in a falling-film evaporator,Food Control,17,325–330,2006.
[7]Karimi M.,Jahanmiri A.,&Azarmi M.Inferential cascade control of multi-effect falling-film evaporator,Food control,18,1036-1042,2007.
[8]Kam K.M.,&Tade M.O..Simulated Nonlinear control studies of five-effect evaporator models,Computer and Chemical Engineering,23,(11-12),1795-1810,2000.
[9]To L.C.,TadéM.O.,&Le G.P.Implementation of a differential geometric nonlinear controller on an industrial evaporator system,Control Engineering Practice,6(11),1309-1319,1998.
[10]Lahtinen S.T.Identification of fuzzy controller for use with a falling-film evaporator,Food Control,12,3,175-180,2001.
[11]Rangaiah G.P.Nonlinear model predictive control of an industrial four-stage evaporator system via simulation,Chemical Engineering Computer Journal,87(3),285-299,2002.
[12]Wang Y.G.,Chai T.Y.,Fu J.,&sun J.(2011).Multiple models adaptive cascade decoupling control for the forced-circulation evaporation system,American Control Conference,5061-5066,2001.
[13]Gelb A.Applied Optimal Estimation,MIT Press,MA,1974.
[14]Boutayeb M.,Rafaralahy H.,&Darouach M.Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems,IEEE Trans.Automat.Control,42,581–586,1974.