Adaptive Zero-Phase Error-Tracking Controllers with Advance Learning

M.M. Mustafa, N.R. Yaacob, and N.A. Nik Mohamed


Adaptive control, zero-phase error, tracking controller, nonminimum phase


Although it is not diffcult to design a phase compensation filter to achieve zero-phase error at all frequencies, designing a gain compensation filter for overall unity gain at all frequencies using a fixed controller is more difficult or even impossible to achieve. This article describes an adaptive algorithm that adaptively adjusts the controller parameters to suit the trajectory signal. The algorithm can be used for both minimum and nonminimum systems. Taking full advantage of the ability to preview the reference trajectory, tuning of the gain compensation filter can be made in advance to further reduce the tracking error when there are changes in the dominant frequency component of the trajectory signal. The advance learning can be done completely before the actual run, and appropriate controller parameters are simply recalled during the actual run to minimize the real-time computation. Advance learning can also be done during the actual run by running the estimator ahead of time to ensure faster convergence; hence there will be smaller tracking error when there are changes in the pattern of the reference trajectory. This look-ahead learning can significantly improve the tracking error.

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