A novel optimal method is developed to improve the identification and estimation of Takagi-Sugeno (TS) fuzzy model. The idea comes from the fact that the main drawback of T-S model is that it can not be applied when the membership functions are overlapped by pairs. This limits the application of the T-S model because this type of membership function has been widely used in the stability and con...

this paper focuses on the non-fragile guaranteed cost control problem for a class of t-s fuzzy time-varying delay systems with local bilinear models. the objective is to design a non-fragile guaranteed cost state feedback controller via the parallel distributed compensation (pdc) approach such that the closed-loop system is delay-dependent asymptotically stable and the closed-loop performance i...

In this paper a Fuzzy Logic Controller (FLC) is proposed for slip minimization and efficiency optimization for the induction motor. Two independent fuzzy logic controllers (FLCs) are implemented using ANFIS toolbox in Matlab Simulink environment. The first FLC is used to control the speed by taking the speed and the speed dervative as input to minimize the motor slip. The second FLC is used to ...

In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit (IMEC) method has been used to generate the input-output data. These input-output data i...

In this paper, an optimal controller for the longitudinal channel of an autonomous helicopter model is designed by blending together two artificial intelligence techniques, genetic algorithms and fuzzy control. An evaluation index that captures the complex, constrained, multiple objective character of the problem was built based on several design requirements expressed in terms of the time resp...

Elevators are the essential transportation tools in high buildings so that elevator group control system (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy rule based intelligent EGCS optimized by genetic algorithm has been proposed where the rules with the corresponding parameters are generated optimally so as to maximize service quality. The...

this paper addresses the design of control charts for both variable ( x chart) andattribute (u and c charts) quality characteristics, when there is uncertainty about the processparameters or sample data. derived control charts are more flexible than the strict crisp case, dueto the ability of encompassing the effects of vagueness in form of the degree of expert’spresumption. we extend the use o...

In this paper, the concept of fuzzy transformation is developed based on fuzzy ordering theory. The clustering property of the fuzzy transformation is investigated by deriving the distribution function of the fuzzy samples and is exploited to address the DCT coded image deblocking problem. In this application, the fuzzy transformation is actually a highly data-adaptive smoothing and sharpening ...

11 A new scheme based on multi-objective hierarchical genetic algorithm (MOHGA) is proposed to extract interpretable rule-based knowledge from data. The approach is derived from the use of multiple objective genetic 13 algorithm (MOGA), where the genes of the chromosome are arranged into control genes and parameter genes. These genes are in a hierarchical form so that the control genes can mani...

We introduce the adaptive fuzzy logic network (AFLN) as the appropriate architecture for the realization of fuzzy membership and fuzzy logic functions. The according AFLN to a given training set is easily constructed and optimized. As their main advantage AFLNs provide for a very eecient sequential implementation of fuzzy systems. This eeciency is achieved by lazy evaluation and the application...