Abstract— The dynamic behavior of power systems is affected by the interactions between linear and nonlinear components. To analyze those complicated power systems, the linear approaches have been widely used so far. Especially, a synchronous generator has been designed by using linear models and traditional techniques. However, due to its wide operating range, complex dynamics, transient perfo...

chaotic systems are nonlinear dynamic systems, the main feature of which is high sensitivity to initial conditions. to initiate a design process in fuzzy model, chaotic systems must first be represented by t-s fuzzy models. in this paper, a new fuzzy modeling method based on sector nonlinearity approach has been recommended for chaotic systems relating to initial condition variations using the ...

Large rotating systems, especially gear drives and gearboxes, occur as parts of many mechanical devices transmitting the torque with relatively small loss of power. With the increased demand for high speed machinery, mathematical modeling and dynamic analysis of gear drives gained importance. Mathematical description of such mechanical systems is a complex task evolving for several decades. In ...

Methods for assessing treatment effects of longitudinal randomized intervention are considered. The focus is on modeling the nonlinear relationship between treatment effects and baseline often observed in prevention programs designed for at-risk populations. Piecewise linear growth modeling was used to study treatment effects during the different periods of development. A multistep multiple-gro...

Most processes in industry are characterized by nonlinear and time-varying behavior. In this context, the identification of mathematical models typically nonlinear systems is vital in many fields of engineering. A variety of system identification techniques are applied to the modeling of processes dynamics. Recently, the identification of nonlinear systems by artificial neural networks has been...

To model nonlinear device behavior at microwave frequencies, accurate large-signal models are required. However, the standard procedure to estimate model parameters is often cumbersome, as it involves several measurement systems (dc, vector network analyzer, etc.). Therefore, we propose a new nonlinear modeling technique, which reduces the complexity of the model generation tremendously and onl...