Self-Tuning Control of a Nonlinear Stochastic Systems Described by a Hammerstein Mathematical Model

In this paper, we developed the parametric estimation and the self-tuning control problem of the nonlinear systems which are described by discrete-time nonlinear mathematical models, with unknown, time-varying parameters, and operative in a stochastic environment. The parametric estimation is realized by using the prediction error method and the recursive least squares techniques. The self-tuning control problem is formulated by minimizing a certain quadratic criterion. An example of numerical simulation is treated in this paper, to test the proposed selftuning control method. General Terms Nonlinear systems; Parametric estimation of a stochastic Hammerstein mathematical models; Recursive Instrumental Variable (RIV) algorithm; self-tuning control of a nonlinear system.