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Zone predictive control based on soft constraint adjustment method


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Zone predictive control based on soft constraint adjustment method
Li Qi’anShang YueLi Yue
School of Information and Control Engineering,Liaoning Shihua University,Fushun 113001,China
soft constraint adjustment methodpredictive controlzone controlcomplicated industrial process controlzone constraintsmultivariable predictive controlquality variablesnormal constraint variablesweightslinear quadratic Gaussian methodinteraction matrix calculations
A soft constraint adjustment method is developed for the multivariable predictive control problem with zone constraint requirements in complicated industrial process control.All output variables are grouped into two categories,namely quality variables and normal constraint variables,according to different control requirements.The variable weights are chosen according to engineering experience.In order to further improve the control performance,the linear quadratic Gaussian method is introduced into the soft constraint adjustment method.The simulation results show that the proposed algorithm doesn’t need to estimate whether the output variables stay within the zone control requirements and avoids complicated interaction matrix calculations,which can satisfy the actual industrial needs more easily.


[1]Perez T,Goodwin G C.Constrained predictive control of ship fin stabilizers to prevent dynamic stall[J].Control Engineering Practice,2008,16(4):482-494.
[2]Maldonado M,Desbiens A R,del Villar R.Potential use of model predictive control for optimizing the column flotation process[J]. International Journal ofMineral Processing,2009,93(1):26-33.
[3]Vesely V,Rosinová D,Foltin M.Robust model predictive control design with input constraints[J].ISA Transactions,2010,49(1):114-120.
[4]González A H,Odloak D.A stable MPC with zone control[J].Journal of Process Control,2009,19(1):110-122.
[6]Bartlett R A,Biegler L T,Backstrom J,et al.Quadratic programming algorithms for largescale model predictive control[J].Journal of Process Control,2002,12(7):775-795.
Xu Zuhua,Zhao Jun,Qian Jixin.Zone model predictive control algorithm using soft constraint method[J].Machine Tool & Hydraulics,2004(3):106-108.
Zou Tao,Li Haiqiang.Twolayer predictive control of multivariable system with integrating element[J].Journal of Zhejiang University(Engineering Science),2011,45(12):2079-2087,2195.
[9]Alvarez L A,Odloak D.Robust integration of real time optimization with linear model predictive control[J].Computers & Chemical Engineering,2010,34(12):1937-1944.
[10]awryńczuk M.Online setpoint optimisation and predictive control using neural Hammerstein models[J].Chemical Engineering Journal,2011,166(1):269-287.
Zhao Chao,Zhang Dengfeng,Xu Qiaoling,et al.Control performance assessment of model predictive control based on statistics analysis of weighted points[J].CIESC Journal,2012,63(12):3971-3977.
Zhou Mengfei,Pan Haitian,Cai Yijun,et al.Constraints adjustment and economic performance coordination based minimum variance benchmark[J].Computers and Applied Chemistry,2012,29(2):181-184.
[13]Prett D M,Morari M.The shell process control workshop[M].Boston,USA:Butterworths,1987:20-31.


Last Update: 2014-06-30