Synthesis of non-parametric type controllers based on I/O data from closed-loop experiment

This paper proposes a data-driven control method with non-parametric map. The proposed method yields the input for tracking control by minimizing a stochastic cost function which consists of I/O data set of the plant. One of the advantages of the proposed method is that it does not need a prior information about the nonlinear system such as their structure. In order to cope with the difficulty in handling the closed-loop I/O data, a penalty term is introduced in the cost function for computing the optimal control input. Experimental validation using a DC motor is performed to show the effectiveness of the proposed controllers.