Implicit Generalized Predictive Control of Multivariable Systems Based on Online Least Square Support Vector Machines of Inverse System

摘要：

　　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.

关键词： online least square support vector machine implicit generalized predictive control dynamic inverse plant CFB boiler

作者: DENG Yi LIU Han WANG Huilong LIU Ding

作者单位: School of Automation and Information Engineering,Xian University of Technology,Xian China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 1793-1799

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）