Closed-loop nonlinear system identification using the vector optimal parameter search algorithm

The vector optimal parameter search (VOPS) and the constrained optimal parameter search (COPS) are recently developed algorithms for closed-loop linear system identification. We extend both algorithms to be applicable to a closed-loop nonlinear system, which is characterized by a vector nonlinear autoregressive model. Monte Carlo simulations of the nonlinear closed-loop system were performed to compare the performance of the VOPS to the widely utilized vector least squares (VLS), the COPS, and the total least squares (TLS) approaches. The relative error and linear transfer functions are computed to determine the accuracy of each method. The clinical applicability of the two extended methods is examined by applying them to a classical physiological closed-loop system, the heart rate baroreflex.