DocumentCode :
234196
Title :
Implicit Generalized Predictive Control of multivariable systems based on online Least Square Support Vector Machines of inverse system
Author :
Deng Yi ; Liu Han ; Wang Huilong ; Liu Ding
Author_Institution :
Sch. of Autom. & Inf. Eng., Xi´an Univ. of Technol., Xi´an, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
1793
Lastpage :
1799
Abstract :
A new Implicit Generalized Predictive Control (IGPC) algorithm based on online Least Square Support Vector Machines (LSSVM) inverse control is proposed. Firstly, an offline model of original nonlinear system is obtained. Online LSSVM is used to identify αth-order inverse dynamic model of nonlinear systems, which can compensate the errors of nonlinear systems caused by offline identification adaptively. Then the model of online αth-order inverse plant is cascaded before positive plant to create an αth-order delay pseudo-linear composite system, which can complete decoupling and linearization of multivariable systems. Then an implicit generalized predictive control is used to control the pseudo-linear composite system. Inputs are constrained in the whole of prediction horizon and control horizon. The simulation and experiment results for the typical nonlinear system and supercritical 600MW CFB process are shown that IGPC of multivariable systems based on online LSSVM have better tracking and strong anti-interference performance.
Keywords :
least squares approximations; multivariable control systems; nonlinear control systems; predictive control; support vector machines; CFB process; IGPC algorithm; LSSVM inverse control; antiinterference performance; delay pseudo linear composite system; implicit generalized predictive control; inverse system; multivariable systems; nonlinear system; offline identification; online least square support vector machines; Control systems; Interconnected systems; MIMO; Mathematical model; Nonlinear systems; Predictive control; Support vector machines; CFB boiler; dynamic inverse plant; implicit generalized predictive control; online least square support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6896901
Filename :
6896901
Link To Document :
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