In this paper, we present an evolutionary multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler, more compact and still accurate linguistic fuzzy models by learning fuzzy inference operators together with Rule Base. The Multiobjective Evolutionary Algorithm proposed generates a set of Fuzzy Rule Based Systems with diff...

In this paper, an adaptive fuzzy controller based on fuzzy neural network is proposed for uncertain nonlinear systems. The main advantages are the simple design, no requirement of system model, and release of fixed universal range of fuzzy output. A fuzzy neural network is applied to on-line identify the control system and provide sufficient information of the adaptive laws for the proposed fuz...

This paper proposes the neural network solution to the indirect vector control of three phase induction motor including an adaptive neuro fuzzy controller. The basic equations and elements of the indirect vector control scheme are given. The proposed control scheme is realized by an adaptive neuro-fuzzy controller and two feed forward neural network. The neuro-fuzzy controller incorporates fuzz...

This paper presents the similarity of a class of adaptive fuzzy controllers and a time dependent single rule controller of TakagiSugeno (TS) model. The class of adaptive fuzzy controllers is one of iterative multilayer structure of single input fuzzy controllers (SIFC). On the other hand, in a time dependent single rule controller of TS model, only one rule can be fired at a time. The result mo...

A fuzzy logic controller equipped with a training algorithm is developed such that the H∞ tracking performance should be satisfied for a model free nonlinear multipleinput multiple-output (MIMO) system with external disturbances. In this paper, a new indirect adaptive interval type-2 fuzzy controller by using fuzzy descriptions to model the plant is proposed to handle the training data corrupte...

In this work, an approach for the development of adaptive fuzzy models is presented. The approach allows to incorporate the system dynamics into the fuzzy membership functions which are defined in terms of a dynamic function with adjustable parameters. These parameters are adapted using a gradient descent based algorithm. Some application examples to illustrate the performance of the dynamical ...

In this paper, an efficient and accurate method for tomatoes sorting will proposed. first we extract features from inputted tomato image and then accurate and appropriate decision on Classification tomatoes using fuzzy the mamdani inference, adaptive fuzzy neural network (anfis) methods for each of that image. In our proposed system adaptive fuzzy neural network (anfis) has less error and syste...

This paper presents a novel adaptive neuro-fuzzy based speed controller for vector controlled induction motor drive. The proposed neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid lear...

Abstract: Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear MIMO system which is very difficult to control. This paper presents adaptive fuzzy output feedback control based on observer for nonlinear HVAC System whose state variables are not available. Fuzzy systems are employed to approximate the unknown nonlinear functions of the HVAC system and the state observer is desig...