This paper introduces a complete framework of Modified Adaptive Fuzzy Inference Engine (MAFIE) and its application. The fuzzy with hybridization schemes has become of research interest in versatile applications over the past decade. The fuzzy hybridizations models are quite popular among practitioners or researchers in various advanced promising fields to help solve problems with a small number...

This work presents a hybrid soft-computing methodology approach for intelligent maximum power point tracking (MPPT) techniques of photovoltaic (PV) system under any expected operating conditions using artificial neural network-fuzzy (neuro-fuzzy). The proposed technique predicts the calculation duty cycle ensuring optimal transfer between PV generator and load. neuro-fuzzy method combines netwo...

inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. in this paper, we derive the horvitz-thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. we then introduce an alternative unbiased estimator, corresponding to post-str...

The purpose of this paper is to create an interval estimation of the fuzzy system reliability for the repairable multistate series-parallel system (RMSS). Two-sided fuzzy confidence interval for the fuzzy system reliability is constructed. The performance of fuzzy confidence interval is considered based on the coverage probability and the expected length. In order to obtain the fuzzy system rel...

Abstract: This paper adresses the problem of fault estimation for continuous-time TakagiSugeno (T-S) fuzzy systems with interval time varying delay. The approach is based on a fuzzy Adaptive Fault Diagnostic Observer (AFDO). By considering an appropriate Lyapunov function, less conservative linear-matrix-inequality (LMI) conditions for the existence of the fault estimator are proposed. Furtherm...

The Cluster-Weighted Modeling (CWM) is emerging as a versatile tool for modeling dynamical systems. It is a mixture density estimator around local models. To be specific, the input regions together with output regions are treated to be Gaussian serving as local models. These models are linked by a linear or non-linear function involving the mixture of densities of local models. The present work...

In this paper, we introduce a linearity test for fuzzy rule-based models in the framework of time series modeling. To do so, we explore a family of statistical models, the regime switching autoregressive models, and the relations that link them to the fuzzy rulebased models. From these relations, we derive a Lagrange multiplier linearity test and some properties of the maximum likelihood estima...

A reinforcement learning-based adaptive optimal fuzzy controller is proposed for maximum power point tracking (MPPT) control of a variable-speed permanent magnet synchronous generator-based wind energy generation system. The algorithm consists critic, an controller, and estimator. critic built based on neuro-fuzzy inference system (ANFIS) network instead the neural as normal to reduce computati...

This work presents a method for contact state estimation using fuzzy clustering to learn contact probability for full, six-dimensional humanoid contacts. The data required for training is solely from proprioceptive sensors endeffector contact wrench sensors and inertial measurement units (IMUs) and the method is completely unsupervised. The resulting cluster means are used to efficiently comput...