Abstract We consider the problem of identifying a parallel Wiener-Hammerstein structure from Volterra kernels. Methods based on kernels typically resort to coupled tensor decompositions However, in case systems, such methods require nontrivial constraints factors decompositions. In this paper, we propose an entirely different approach: by using special sampling (operating) points for Jacobian n...

In this research study, one of the most crucial automotive engineering problems is intended to be solved. The necessity of tire pressure monitoring system is beyond doubt. Such systems are now provided relying on expensive sensors. In this study an indirect tire pressure monitoring system is proposed, utilizing identification techniques, which will reduce the cost of monitoring considerably in ...

This paper presents a new formulation of extremum-seeking control for discrete-time Wiener– Hammerstein plants. A novel method of analysis using Linear Parameter-Varying (LPV) system theory demonstrates semi-global stability of the control scheme. Assuming only limited plant knowledge, the stability result ensures convergence of the plant output in steady state to a point in an arbitrarily smal...

This article deals with the black-box modeling of synchronous generators based on artificial neural networks (ANN). The ANN is applied to define relationship between excitation and terminal generator voltage values, Levenberg–Marquardt algorithm used for determining weight coefficients. relation made response reference step changes. proposed approach checked using experimental results obtained ...