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...

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct...

This paper aims to develop robust adaptive fuzzy control techniques to improve tracking performance, where both the tracking error and the modeling error are utilized to adjust system parameters. A hybrid adaptive control scheme including a H∞ compensator is proposed which makes the tracking performance faster and more reliable. Performance analysis is given by using Lyapunov theory. In our pro...

The problem of manipulator control is a highly complex problem of controlling a system which is multi-input, multioutput, non-linear and time variant. In this paper some adaptive fuzzy, and a new hybrid fuzzy control algorithm have been comparatively evaluated through simulations, for manipulator control. The adaptive fuzzy controllers consist of self-organizing, self-tuning, and coarse/fine ad...

This study developed an enhanced adaptive self-organizing fuzzy slidingmode controller (EASFSC) for robotic systems. Rather than using the output error and the error change of the system, the EASFSC uses a sliding surface and its differential as the input variables of a fuzzy logic controller (FLC) in a self-organizing fuzzy controller (SOFC) to generate a control input through fuzzy operation....

This paper describes background and design of a model free adaptive Fuzzy Logic Controller. Controller Error Scaling Factor adaptation uses principle of balancing Error and Change of Error actions. Adaptation proceeds only if prescribed set of conditions is satisfied. Controller Scaling Factor for Change of Output adaptation uses weighted average of correction from oscillation index and process...

Abstract: In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor,...

In this paper, a novel state error feedback sliding controller is proposed. In the controller, an optimal feedback gain is required and in this study it is assumed to be unknown. Usually, a rudimentary feedback gain is used. Besides, in order to approximate the state error feedback sliding controller with the optimal feedback gain, an adaptive fuzzy system is employed. Thus, the proposed contro...

Conventional control depends on the mathematical model of the plant being controlled. When this model is uncertain, intelligent controllers promise better performance. This paper presents a theoretical study on model reference adaptive fuzzy logic controller for vector controlled Permanent Magnet Synchronous Motor (PMSM) drive. In the proposed system, Fuzzy Logic Control (FLC) is used to implem...

Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an ...