In this paper we propose an approach to improve the direct torque control (DTC) of an induction motor (IM). The proposed DTC is based on fuzzy logic technique switching table, is described compared with conventional direct torque control (DTC). To test the fuzzy control strategy a simulation platform using MATLAB/SIMULINK was built which includes induction motor d-q model, inverter model, fuzzy...

Abstract This paper addresses the problem of adaptive fuzzy tracking control for MIMO uncertain nonlinear time-delay systems. The control scheme combines adaptive fuzzy control with  H control. Adaptive time-delay fuzzy logic systems are constructed and used to approximate the uncertain unknown timedelay functions. The  H compensator is designed to eliminate fuzzy approximation errors and ext...

this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy si...

We investigate adaptive methods for optimal control problems with finitely many control parameters. We analyze a-posteriori error estimates based on verification of second-order sufficient optimality conditions. Reliability and efficiency of the error estimator is shown. The estimator is used in numerical tests to guide adaptive mesh refinement.

Doubly-fed induction generator (DFIG) based wind turbines with traditional maximum power point tracking (MPPT) control provide no inertia response under system frequency events. Recently, the DFIG wind turbines have been equipped with virtual inertia controller (VIC) for supporting power system frequency stability. However, the conventional VICs with fixed gain have negative effects on inter-ar...

An adaptive fuzzy gain scheduling scheme for robotic arm has been proposed. This paper focus on adaptive fuzzy based tracking and gain controller algorithm for obtaining the joints position relative to the desired trajectory, which drives static and different time variations on the environmental changes. We able to estimate them at any point of time, when t >0 or alternatively, starting from th...

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameter...

This paper proposes a fuzzy channel allocation controller (FCAC) for hierarchical cellular systems. The FCAC mainly contains a fuzzy channel allocation processor (FCAP) which is designed to be in a two-layer architecture that consists of a fuzzy admission threshold estimator in the first layer and a fuzzy channel allocator in the second layer. The FCAP chooses the handoff failure probability, d...

In this paper, we propose a scalar variable formation of fuzzy regression model based on the axiomatic credibility measure foundation. The fuzzy estimation for fuzzy regression coefficients is investigated. A general M-estimation criterion is developed under Maximum Fuzzy Uncertainty Principle, which resulted in weighted Normal equation with adjusted term for M-estimator of the regression coeff...

Cancer research is one of the major research areas in the medical field. Adaptive Neuro Fuzzy Interference System is used for the classification of Cancer. This algorithm compared with proposed algorithm of Adaptive Neuro Fuzzy Interference system with Runge Kutta learning method for the best classification of cancer. It is one of the better techniques for the classification of the cancer. The ...