Journal of the Korean Society of Manufacturing Process Engineers (한국기계가공학회지)

The Korean Society of Manufacturing Process Engineers (한국기계가공학회)
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Asymptotic Output Tracking of Non-minimum Phase Nonlinear Systems through Learning Based Inversion

학습제어를 이용한 비최소 위상 비선형 시스템의 점근적 추종

  • Received : 2022.06.26
  • Accepted : 2022.07.11
  • Published : 2022.08.31
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Abstract

Asymptotic tracking of a non-minimum phase nonlinear system has been a popular topic in control theory and application. In this paper, we propose a new control scheme to achieve asymptotic output tracking in anon-minimum phase nonlinear system for periodic trajectories through an iterative learning control with the stable inversion. The proposed design method is robust to parameter uncertainties and periodic external disturbances since it is based on iterative learning. The performance of the proposed algorithm was demonstrated through the simulation results using a typical non-minimum nonlinear system of an inverted pendulum on a cart.

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References

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