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Adaptive neural control for nonstrict-feedback time-delay systems with input and output constraints

  • Wenjie Si
  • Xunde Dong
Original Article
  • 187 Downloads

Abstract

An adaptive tracking control is investigated for a class of nonstrict-feedback nonlinear systems with time delays subject to input saturation nonlinearity and output constraint. First, the Gaussian error function is used to express the continuous differentiable asymmetric saturation model, and a barrier Lyapunov function is designed to ensure that the output parameters are restricted. Then, an appropriate Lyapunov–Krasovskii functional is chosen to deal with the unknown time-delay terms, and the neural network is used to model the unknown nonlinearities. Finally, based on Lyapunov stability theory, an adaptive neural controller is designed to establish the closed-loop system stability. The example is provided to further illustrate the effectiveness and applicability of the proposed approach.

Keywords

Adaptive neural control Nonlinear systems Non-strict-feedback Time-delay Lyapunov-Krasovskii functional 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Automation Science and EngineeringSouth China University of TechnologyGuangdongChina

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