Abstract: This paper presents the design methods for the designing and simulation of implication function (mamdani) using two stage CMOS operational amplifier in SPICE. This paper also presents how the first three steps of fuzzy system i.e. fuzzification, rule composition and implication process are merged and get the output for each rule. I have also calculated the electrical parameters like s...

The Cerebellar Model Articulation Controller (CMAC) and fuzzy systems have been active areas of research since its initial introduction. Fuzzy CMAC is basically a CMAC that is coupled with a fuzzy system. This paper presents the incorporation of fuzzy systems into CMAC with Approximate Analogical Reasoning Scheme (AARS) as its inference rules and Discrete Incremental Clustering (DIC) as its tec...

Controller design strategy for Takagi-Sugeno (T-S) fuzzy systems is considered in the two-degree-of-freedom (TDOF) framework. Firstly, coprime factorization described in the state space formulas for T-S fuzzy systems is introduced based on a common Lyapunov function. Secondly, based on this coprime factorization, TDOF framework for LTI systems is extended to be applied to T-S fuzzy systems. Con...

This paper describes a self-tuning Neuro-fuzzy Controller by Genetic Algorithm (NFCGA) applied to a coupled-tank fluid level control. The controller use a simplified fuzzy algorithm which based on the Radial Basis Function neural network (RBF). Genetic Algorithm (GA) is used to tune simultaneously all the parameters of controller from a random state. A plant model is used initially to tune the ...

There are several techniques to control of an uncertain nonlinear system. A typical approach is sliding mode control technique [14]. In the sliding mode technique, the proper transformation of tracking errors to generalize errors is introduced, so that n order tracking problem can be transformed into an equivalent first order stabilization problem [16]. The sliding-mode control employs a discon...

Abstract Fuzzy set and neutrosophic are two efficient tools to handle the uncertainties vagueness of any real-world problems. Neutrosophic is more capable than fuzzy deal a real-life problem. This research paper introduces some new concept single-valued graph (SVNG). We have also presented different operations on SVNG such as rejection, symmetric difference, maximal product, residue product wit...

Recently, the Takagi-Sugeno fuzzy controllers [3] have been applied to nonlinear systems (see, for example, [3] and [4]). In these studies, a nonlinear plant was represented by a set of linear models interpolated by membership functions and then a model-based fuzzy controller was developed. This technique seems particularly suitable for the control of complex nonlinear systems since the dynamic...

The problem of finding the digital convex fuzzy hull of a digital fuzzy set, whose support is made of some digital points (centroids) in Z, is considered here. A region is DL−convex if, for any two pixels belonging to it, there exists a digital straight line between them, all of whose pixels belong to the region. An algorithm how to compute the DL−convex hull of a digital region is described. A...

Based on active disturbance rejection control (ADRC) and fuzzy logic control, a control scheme for attitude maneuver control of spacecraft is proposed. In which a maneuver path is planned to reduce overshoot and improve rapidity, and an extended state observer is designed to cope with unknown disturbances and parameter uncertainties. Furthermore, in order to improve dynamic performance of the c...

This paper describes a VLSI architecture for classification of multiand hyperspectral imagery using Fuzzy Logic with trapezoidal membership functions. The fuzzy classifier is implemented using a rule-based approach, where each class is defined as a set of sub rules. There is only one sub rule associated to each band within a class. Each sub rule is implemented as a dedicated parallel hardware. ...