Adaptive identification and prediction control for time delay nonlinear systems based on neural networks

Jing Na*, Xuemei Ren

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

This paper presents the identification, prediction and control design for nonlinear strict-feedback systems with an input time-delay. The system is firstly transformed into a normal form by defining new state variables. A dynamical identification with a neural network (NN) is proposed to estimate the system states. The predictive NN weights are obtained without iterative calculations and utilized in constructing the adaptive predictor. Feedback control design using the predictive states is finally studied. Simulations are included to validate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages685-688
Number of pages4
Publication statusPublished - 1 Dec 2010
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, United Kingdom
Duration: 4 Feb 20106 Feb 2010

Conference

Conference15th International Symposium on Artificial Life and Robotics, AROB '10
CountryUnited Kingdom
CityBeppu, Oita
Period4/02/106/02/10

Keywords

  • Neural networks
  • Nonlinear predictor
  • State observer
  • Time-delay systems

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  • Cite this

    Na, J., & Ren, X. (2010). Adaptive identification and prediction control for time delay nonlinear systems based on neural networks. In Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10 (pp. 685-688)