road transportation by way of automobiles is a very convenient means of transportation. today, the most detrimental consequence of developing transportation systems in a country is traffic accident that places a huge financial burden on society. this paper investigates the role of information systems in transportation safety that leads to improved planning and operation of the transportation sy...

The purpose of this paper is to study the description of power system QV curves by using the method of fuzzy modeling for analysis of voltage stability. Voltage instability of power system comes from increasing load rapidly, and causes bus voltage to drop. When voltage is out of control and it can be voltage collapse. The QV curve can identify voltage stability limit, and it determine robustnes...

System modeling concerns modeling the operation of an unknown system from a set of measured input-output data and/or some prior knowledge (e.g., experience, expertise, or heuristics) about the system. It plays a very important role and has a wide range of applications in various areas such as control, power systems, communications, networks, machine intelligence, etc. To understand the underlyi...

In order to build accurate model for complicated nonlinear system in engineering, like boiler–turbine system, a novel fuzzy-modeling approach is proposed, which is based on a new fuzzy c-regression model (NFCRM) clustering algorithm and is able to determine the right number of rules automatically. In this method, NFCRM is applied to build the fuzzy structure and then identify the premise parame...

Takagi-Sugeno (TS) fuzzy modeling and control techniques are applied to the classical nonlinear Ball and Beam problem. The nonlinear model is segmented to different local linear models. Local controllers are hence designed using LMI theory for achieving a robust control behavior for ball position. TS fuzzy modeling is applied to generate suitable fuzzy models, and the associated controllers. Us...

In this paper, we propose a new dynamical fuzzy modeling technique for SISO complex systems. It is seen that, the whole state-space of a complex system is divided into subspaces and a linear time-invariant (LTI) model is then used tu approximate the complex system in each subspace. However, the global dynamical fuzzy model of the complex system is derived by aggregating all subsystem poles and ...

System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused o...

This study addresses the problem of modeling physiological systems using fuzzy logic. As an application we consider the problem of modeling the anesthetics process. In particular we consider the problem of modeling the evolution of the bispectral index in patients undergoing anesthesia with intravenous propofol. An identification based on fuzzy inference system is proposed. One of the main adva...