This paper considers the problem of designing a controller for an unknown plant based on input/output measurements. The new design method we propose is direct (no model identification of the plant is needed) and can be applied using a single set of data generated by the plant, with no need for specific experiments nor iterations. It is shown that the method searches for the global optimum of the design criterion and that, in the case of restricted complexity controller design, the achieved controller is a good approximation of the restricted complexity global optimal controller. A simulation example shows the effectiveness of the method
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