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Through analysis of the time-delay characteristics of stabilized and tracking platform position tracking loop and of attitude disturbance exciting in stabilization and tracking platform systems, a compound control method based on adaptive fuzzy-grey prediction control (CAGPC) is proposed to improve the disturbance suppression performance and system response of stabilized and tracking platform system. Firstly, the feedforward controller which is to improve disturbance suppression performance of stabilized and tracking platform servo system and aiming at the external disturbances is introduced. Secondly, aiming at the disadvantages of conventional fixed step size of Fuzzy-grey prediction and the prediction error forecast model has, an adaptive adjustment module adjusting the prediction step and comprehensive error weight at the same time is proposed, according to the actual control system error and the prediction error, the Fuzzy-grey prediction step and the prediction error weights are regulated while to improve the control precision and the adaptability of the system prediction model; At last, Numerical simulation results and the stabilized and tracking platform experimental verification illustrate that the compound control method can improve the stable platform servo system response and the ability of suppress external disturbances and the CAGPC control method has better performance in the stabilized and tracking platform system.

A novel servo control method based on feedforward control – Fuzzy-grey predictive controller for stabilized and tracking platform system