Maximum likelihood gradient-based iterative estimation algorithm for a class of input nonlinear controlled autoregressive ARMA systems

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• 作者：Feiyan Chen (1)
  Feng Ding (1)
  Junhong Li (2)
  
  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) ; Jiangnan University ; Wuxi ; 214122 ; People鈥檚 Republic of China
  2. School of Electrical Engineering ; Nantong University ; Nantong ; 226019 ; People鈥檚 Republic of China
  
• 关键词：Parameter estimation ; Maximum likelihood ; Stochastic gradient ; Simulation
• 刊名：Nonlinear Dynamics
• 出版年：2015
• 出版时间：January 2015
• 年：2015
• 卷：79
• 期：2
• 页码：927-936
• 全文大小：378 KB
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• 刊物类别：Engineering
• 刊物主题：Vibration, Dynamical Systems and Control
  Mechanics
  Mechanical Engineering
  Automotive and Aerospace Engineering and Traffic
  
• 出版者：Springer Netherlands
• ISSN：1573-269X

文摘

This paper considers the parameter estimation problem for an input nonlinear controlled autoregressive ARMA model. The basic idea is to combine the maximum likelihood principle and the gradient search and to present a maximum likelihood gradient-based iterative estimation algorithm. The analysis and simulation results show that the proposed algorithm can effectively estimate the parameters of the input nonlinear controlled autoregressive ARMA systems.