Stability Analysis and Performance Evaluation of an Adaptive Neural Controller

  • Dingguo Chen
  • Jiaben Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)


In this paper, a neural network based adaptive controller is designed for a class of nonlinear systems. The offline neural network training and on-line neural network tuning are integrated to assure that not only the stability of the resulting closed-loop control system is guaranteed, but also the reasonable tracking performance is achieved. The adaptation of the parameters of neural networks is handled based on the robust adaptive control design methodology. The off-line training step incurs additional cost and maybe inconvenience compared to direct on-line neural network parameters tuning. However, the stability analysis and performance evaluation have a more solid basis; and the weight adaptation laws are different than those existing in the literature and bear more practical meaning and significance.


Neural Network Hide Layer Adaptive Controller Neural Network Training Neural Network Parameter 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Dingguo Chen
    • 1
  • Jiaben Yang
    • 2
  1. 1.Siemens Power Transmission and Distribution Inc.Brooklyn ParkUSA
  2. 2.Department of AutomationTsinghua UniversityBeijingChina

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