The paper presents a study upon the possibility to use adaptive-network-based fuzzy inference method (ANFIS) in the identification of distributed parameter systems, implementing a distributed sensor network in the system. Some main properties of different identification methods are presented with possible application. The fuzzy systems, implemented using rule bases, fuzzy values, membership fun...

In this paper, a stable adaptive type-2 fuzzy tracking control equipped with sliding mode and Lyapunov synthesis approaches is proposed to attenuate the effects from unmodeled dynamics, external disturbance and approximation errors for nonlinear SISO systems. By employing adaptive fuzzy-neural control theory incorporated with Lyapunov stability criterion, the adaptive laws will be derived for a...

A flexible-joint robot manipulator is a complex system because it is nonlinear, multivariable, highly coupled along with joint flexibility and uncertainty. To overcome flexibility, several methods have been proposed based on flexible model. This paper presents a novel method for controlling flexible-joint robot manipulators. A novel control law is presented by compensating flexibility to form a...

Abstract: In this paper an application of the adaptive neuro-fuzzy inference system has been introduced to predict the behavior of a chaotic robot. The chaotic mobile robot implies a mobile robot with a controller that ensures chaotic motions. Chaotic motion is characterized by the topological transitivity and the sensitive dependence on initial conditions. We have used the controller such that...

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking perf...

The real world Parkinson’s disease (PD) is a chronic progressive neurological disease that affects a small area of nerve cells called neurons in the area of the brain called the substantia nigra. Medical Expert System technique is a solution of this problem. This paper summarizes regarding the classification of Parkinson’s disease by using adaptive neuro-fuzzy inference engines. The learning fo...

In this paper, an adaptive fuzzy tracking control approach is proposed for a class of single-inputsingle-output (SISO) nonlinear systems in which the unknown continuous functions may be nonlinearlyparameterized. During the controller design procedure, the fuzzy logic systems (FLS) in Mamdani type are applied to approximate the unknown continuous functions, and then, based on the minimal learnin...

An indirect adaptive fuzzy power system stabilizer (IDFPSS) is proposed in this paper. It consists of A fuzzy identifier and a feedback linearizing controller. The objective is to damp local and inter-area oscillations that occur following power system disturbance. The effectiveness of the proposed technique is illustrated by applying the IDFPSS to a two-area four-machine system that is typical...

This paper addresses the problem of designing fin control for the ship roll stabilization. A novel adaptive robust fuzzy control (ARFC) algorithm is presented for ship roll nonlinear system with unstructured uncertainties. In the algorithm, the Takagi-Sugeno type fuzzy logic systems are employed to approximate uncertain functions in the systems, and a systematic procedure is developed for the s...

In this paper, the principle of sliding mode control is used as a basis to develop an adaptive fuzzy controller for uncertain dynamic time-delayed systems with series nonlinearities. The control method provides a simple way to achieve asymptotic stability of the uncertain time-delayed system. Other attractive features of the method include a minimal realization of the adaptive fuzzy controller ...