Multi-innovation Generalized Extended Stochastic Gradient Algorithm for Multi-Input Multi-Output Nonlinear Box-Jenkins Systems Based on the Auxiliary Model

摘要：

An auxiliary model based multi-innovation generalized extended stochastic gradient algorithm is developed for multivariable nonlinear Box-Jenkins systems. The basic idea is to construct an auxiliary model using the measured data and to replace the unknown terms in the information vector with their estimates, i.e., the outputs of the auxiliary model. The proposed algorithm can give high accurate parameter estimation compared with existing stochastic gradient algorithms. A simulation example is given.

关键词： Stochastic gradient Multi-input multi-output systems Multi-innovation identification Box-Jenkins systems Recursive identification

作者: Jing Chen Xiuping Wang

作者单位: Control Science and Engineering Research Center, Jiangnan University,Wuxi, PR China 214122 Wuxi Professional College of Science and Technology, Wuxi, PR China 214028

会议类型: 国际会议

会议名称: International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)

会议地点: 无锡

会议语种:英文

页码: 136-146

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）