A Global-Local Mapping Approximation method is presented in this paper for identifying discrete systems using input-output data. The method is based on the idea that any nonlinear system can be represented as a sum of a discrete linear model and unmodeled nonlinearities. Linear system is then perturbed by a nonlinear term which represents the system nonlinearities that are not captured by the l...

the aim of this paper is to investigate a novel approach for output feedback damping controller design ofstatcom in order to enhance the damping of power system low frequency oscillations (lfo). the design ofoutput feedback controller is considered as an optimization problem according with the time domain-basedobjective function which is solved by a honey bee mating optimization algorithm (hbmo...

in this paper, a new algorithm for system identification based on frequency response is presented. in this method, given a set of magnitudes and phases of the system transfer function in a set of discrete frequencies, a system of linear equations is derived which has a unique and exact solution for the coefficients of the transfer function provided that the data is noise-free and the degrees of...

This paper presents an integrated framework for system identification. This framework provides a useful tool for obtaining and validating system models. Once the model is synthesized, a validation process is applied to a real-time implementation within the Real-Time Virtual Test Bed (RTVTB). As a demonstration, a 3 rd -order filter is taken as the system under test (SUT). The system identificat...

System identiication of linear dynamical systems using so-called subspace methods consists of two main steps. First, a signal subspace estimate is found. This usually corresponds to estimating the range space of the extended observability matrix. Then the system parameters are estimated from the subspace estimate. The main result of this note is explicit excitation conditions on the input signa...

Identifiability is important to guarantee convergence in system identification applications, and observability is important in applications such as control and diagnosis. In this paper, recent results on analysis of nonlinear differentialalgebraic equations are used to derive criteria for local identifiability and local weak observability for such models. The criteria are based on rank tests. E...