Support vector machine-based multi-model predictive control
Zhejing BA
Youxian SUN
摘要：In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results.
机标关键词：model predictive controlsupport vector machineoperating conditionssimulation resultscontroller design
资助基金：the 973 Program of China(2002CB312200)the National Science Foundation of China(60574019)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 305-310 )
英文信息