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In this paper, a parameter tuning of a state predictive servo system with a full state observer for linear timedelay systems is proposed within the data-driven control framework. Here, fictitious reference iterative tuning (which is abbreviated as FRIT), which is a controller parameter tuning method yielding the desirable parameter with only one-shot experimental data, is applied for the achievement of the desired tracking property. Particularly, it is also shown that the cost function to be minimized here is deeply related to the improvement of the parameter with respect to not only the desired closed loop property but also the attainment of more appropriate model of a plant. Finally, to show the validity and effectiveness of our result, a numerical example is illustrated.

FRIT Based Simultaneous Update of Controller and Model on State Predictive Servo Systems with Full State Observers for Linear Time-delay Systems