A GLOBAL NONLINEAR INSTRUMENTAL VARIABLE METHOD FOR IDENTIFICATION OF CONTINUOUS-TIME SYSTEMS WITH UNKNOWN TIME DELAYS

This paper considers the identification problem of continuous-time systems with unknown time delays from sampled input-output data. An iterative global separable nonlinear least-squares (GSEPNLS) method which estimates the time delays and transfer function parameters separably is derived, by using stochastic global-optimization technique to avoid convergence to a local minimum. Futhermore, the GSEPNLS method is modified to a novel global separable nonlinear instrumental variable (GSEPNIV) method to yield consistent estimates if the algorithm converges to the global minimum. Simulation results show that the proposed method works quite well.