Online identification of continuous-time systems with multiple-input time delays from sampled data using sequential nonlinear least square method from sampled data

This research considers the problem of online identification of continuous-time system with multiple unknown time delays from sampled data. The presented algorithm estimates, simultaneously, the linear parameters and the multiple time delays. Therefore, a Sequential Nonlinear Least Square algorithm is used. Indeed, we propose a new formulation of the identification problem which permits the definition of the time delays and the parameters in the same estimated vector. Numerical example is presented to illustrate the robustness of the proposed algorithm.