Iterative controller optimization for nonlinear systems

Recently, a data-driven model-free control design method has been proposed in [4, 6]. It is based on the minimization of a control criterion with respect to the controller parameters using an iterative gradient technique. In this paper, we extend this method to the case where both the plant and the controller can be nonlinear. It is shown that an estimate of the gradient can be constructed using only signal based information. It is also shown that by using open loop identification techniques, one can obtain a good approximation of the gradient of the control criterion while performing fewer experiments on the actual system.