In this paper, the effect of Static VAr Compensator (SVC) parameters on the nonlinear interaction of steam power plant turbine-generator set is studied using the Modal Series (MS) method. A second order representation of a power system equipped with SVC is developed and then by MS method the nonlinear interaction of torsional modes is assessed under various conditions and the most influencing f...

In the present study, nonlinear vibration of coupled carbon nanotubes (CNTs) in presence of surface effect is investigated based on nonlocal Euler-Bernoulli beam (EBB) theory. CNTs are embedded in a visco-elastic medium and placed in the uniform longitudinal magnetic field. Using von Kármán geometric nonlinearity and Hamilton’s principle, the nonlinear higher order governing equations are deriv...

neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

In the current study, the effects of Casimir force and squeeze film damping on pull-in instability and dynamic behavior of electrostatically actuated nano and micro electromechanical systems are investigated separately. Linear elastic membrane theory is used to model the static and dynamic behavior of the system for strip, annular and disk geometries. Squeeze film damping is modeled using nonli...

This paper presents a practical implementation for a new formula of nonlinear PID (NPID) control. The purpose of the controller is to accurately trace a preselected position reference of one stage servomechanism system. The possibility of developing a transfer function model for experimental setup is elusive because of the lack of system data. So, the identified model has been developed via gat...

â  abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...