A novel tracker for a class of sampled-data nonlinear systems

Jason Sheng-Hon Tsai, Fu Ming Chen, Shu-Mei Guo, Chia Wei Chen, Leang San Shieh

研究成果: Article

7 引文 斯高帕斯(Scopus)

摘要

In this paper, a novel observer/Kalman filter identification (OKID) based iterative learning control (ILC) for a class sample-data nonlinear system is proposed and supplies a good tracking performance in both the transient and steady-state phase. The proposed observer-based digital redesign tracker can suppress the uncertainties and the nonlinear perturbations. First, even without resetting the identical initial condition the optimal linear model of the analog nonlinear system is constructed at the operating point. The operating point is generated due to the analog observer updated by the well-designed analog OKID-ILC nonlinear system. Thereafter, the linear quadratic regulator design technique with a high-gain property is applied to design an analog observer-based tracker of the optimal linear model. Finally, the proposed approach for the analog system is then extended to the case for a class of sampled-data nonlinear systems.

原文English
頁(從 - 到)81-101
頁數21
期刊JVC/Journal of Vibration and Control
17
發行號1
DOIs
出版狀態Published - 2011 一月 1

    指紋

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Automotive Engineering
  • Aerospace Engineering
  • Mechanics of Materials
  • Mechanical Engineering

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