Model predictive control synthesis algorithm based on polytopic terminal region for Hammerstein-Wiener nonlinear systems

Yan Li , Xue-yuan Chen , Zhi-zhong Mao

Journal of Central South University ›› 2017, Vol. 24 ›› Issue (9) : 2028 -2034.

PDF
Journal of Central South University ›› 2017, Vol. 24 ›› Issue (9) : 2028 -2034. DOI: 10.1007/s11771-017-3612-8
Article

Model predictive control synthesis algorithm based on polytopic terminal region for Hammerstein-Wiener nonlinear systems

Author information +
History +
PDF

Abstract

An improved model predictive control algorithm is proposed for Hammerstein-Wiener nonlinear systems. The proposed synthesis algorithm contains two parts: offline design the polytopic invariant sets, and online solve the min-max optimization problem. The polytopic invariant set is adopted to replace the traditional ellipsoid invariant set. And the parameter-correlation nonlinear control law is designed to replace the traditional linear control law. Consequently, the terminal region is enlarged and the control effect is improved. Simulation and experiment are used to verify the validity of the wind tunnel flow field control algorithm.

Keywords

Hammerstein-Wiener nonlinear systems / model predictive control / polytopic terminal constraint set / parametercorrelation nonlinear control / stability / linear matrix inequalities (LMIs)

Cite this article

Download citation ▾
Yan Li, Xue-yuan Chen, Zhi-zhong Mao. Model predictive control synthesis algorithm based on polytopic terminal region for Hammerstein-Wiener nonlinear systems. Journal of Central South University, 2017, 24(9): 2028-2034 DOI:10.1007/s11771-017-3612-8

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

WangD, DingF. Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems [J]. Computers & Mathematics with Applications, 2008, 56(12): 3157-3164

[2]

WangD, DingF. Hierarchical least squares estimation algorithm for Hammerstein-Wiener systems [J]. IEEE Signal Processing Letters, 2012, 19(12): 825-827

[3]

SungS W, JeC H, LeeJ, LeeD H. Improved system identificat ion method for Hammerstein-Wiener processes [J]. Korean Journal of Chemical Engineering, 2008, 25(4): 631-636

[4]

PatcharaprakitiN, KirtikaraK, MonyakulV, ChenvidhyA D, ThongpronJ, SangswangA. Modeling of single phase inverter of photovoltaic system using Hammerstein-Wiener nonlinear system identification [J]. Current Applied Physics, 2010, 10(3): 532-536

[5]

XiY-g, LiD-wei. Fundamental philosophy and status of qualitative synthesis of model predictive control [J]. Acta Automatica Sinica, 2008, 34(10): 1225-1234

[6]

PatikirikoralaT, WangL, ColmanA, HanJ. Hammerstein-Wiener nonlinear model based predictive control for relative QoS performance and resource management of software systems [J]. Control Engineering Practice, 2012, 20(1): 49-61

[7]

van den BloemenH H J, BoomT J J, VerbruggenH B. Model-based predictive control for Hammerstein-Wiener systems [J]. International Journal of Control, 2001, 74(5): 482-495

[8]

KouvaritakisB, RossiterJ A, SchuurmansJ. Efficient robust predictive control [J]. IEEE Transactions on Automatic Control, 2000, 45(8): 1545-1549

[9]

WanZ, KothareM V. An efficient off-line formulation of robust model predictive control using linear matrix inequalities [J]. Automatica, 2003, 39(5): 837-846

[10]

DingB-c, YangPeng. Synthesizing off-line robust model predictive controller based on nominal performance cost [J]. Acta Automatica Sinica, 2006, 32(2): 304-310

[11]

LiY, ChenX-y, MaoZ-z, YuanPing. An improved constrained model predictive control approach for Hammerstein-Wiener nonlinear systems [J]. Journal of Central South University, 2014, 21(3): 926-932

[12]

YauH T. Generalized projective chaos synchronization of gyroscope systems subjected to deadzone nonlinear inputs [J]. Physics Letters A, 2008, 372(14): 2380-2385

[13]

WangD, ChuY, YangG, DingF. Auxiliary model based recursive generalized least squares parameter estimation for Hammerstein OEAR systems [J]. Mathematical and Computer Modelling, 2010, 52(1): 309-317

[14]

ZhangY-w, GuiW-hua. Compensation for secondary uncertainty in electro-hydraulic servo system by gain adaptive sliding mode variable structure control [J]. Journal of Central South University of Technology, 2008, 15(2): 256-263

AI Summary AI Mindmap
PDF

112

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/