Neural Network Based Multiple Model Adaptive Predictive Control for Teleoperation System

  • Qihong Chen
  • Jin Quan
  • Jianjun Xia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4491)


Environment model and communication time delays of a teleoperation system are variant usually, which will induce bad performance, even instability of the system. In this paper, neural network based multiple model adaptive predictive control method is proposed to solve this problem. The whole control system is composed of predictive controller and decision controller. First of all, neural network model set of any possible environment is built up, and time forward state observer based predictive controllers are designed for all models. In succession, decision controller is designed to adaptive switch among all predictive controllers according to performance target. This method can ensure stability and performance of the system. Finally, simulation results show effectiveness of the proposed method.


Environment Model Predictive Controller Master Controller Decision Controller Performance Index Function 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Qihong Chen
    • 1
  • Jin Quan
    • 2
  • Jianjun Xia
    • 1
  1. 1.School of Automation, Wuhan University of Technology, Wuhan 430070China
  2. 2.School of Electronics and Information Engineering, Tongji University, Shanghai 200092China

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