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Output Feedback Adaptive Dynamic Surface Control of Permanent Magnet Synchronous Motor with Uncertain Time Delays via RBFNN

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  • Shaohua Luo
  • Jiaxu Wang
  • Zhen Shi
  • Qian Qiu

Abstract

This paper focuses on an adaptive dynamic surface control based on the Radial Basis Function Neural Network for a fourth-order permanent magnet synchronous motor system wherein the unknown parameters, disturbances, chaos, and uncertain time delays are presented. Neural Network systems are used to approximate the nonlinearities and an adaptive law is employed to estimate accurate parameters. Then, a simple and effective controller has been obtained by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed control has been illustrated through simulation results.

Suggested Citation

  • Shaohua Luo & Jiaxu Wang & Zhen Shi & Qian Qiu, 2014. "Output Feedback Adaptive Dynamic Surface Control of Permanent Magnet Synchronous Motor with Uncertain Time Delays via RBFNN," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-12, January.
    • Handle: RePEc:hin:jnddns:315634
    DOI: 10.1155/2014/315634
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