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The continuous-time generalized predictive control (CGPC) and the quantitative feedback theory (QFT) are used together to control the plant with high uncertainty. QFT conquers the plant uncertainty and stabilizes the system in the inner loop without affecting the nominal performance based on the generalized internal model control (GIMC) structure. CGPC is used to obtain the necessary control performance in the outer loop. According to several given sufficient conditions, the available tuning parameters of CGPC are selected to make the system robustly stable. Finally, an example is given to show how to use this technique; and it is shown that this combined approach gets better performance than if only one of them is used.
The continuous-time generalized predictive control (CGPC) and the quantitative feedback theory (QFT) are used together to control the plant with high uncertainty. QFT conquers the plant uncertainty and stabilizes the system in the inner loop without affecting the nominal performance based on the generalized internal model control (GIMC) structure. CGPC is used to obtain the necessary control performance in the outer loop. Finally, an example is given to show how to use this technique; and it is shown that that combined approach gets better performance than if only one of them is used.