A Supervisory Robust Adaptive Fuzzy Controller
نویسندگان
چکیده
A fuzzy controller equipped with an adaptive algorithm and two supervisors is developed in this work to achieve tracking performances for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. The convergence of the training algorithm is guarantied by a gradient projection law. The effect of both the approximation errors and the external disturbances is attenuated to a prescribed level thanks to H∞ control. The convergence of the tracking error toward zero is guarantied by a supervisor where linguistic rules are used to accelerate the convergence speed. Copyright © 2002 IFAC
منابع مشابه
Enhancement of Robust Tracking Performance via Switching Supervisory Adaptive Control
When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the unce...
متن کاملCMAC-based previous step supervisory control schemes for relaxing bound in adaptive fuzzy control
In this paper, a novel scheme of incorporating a learning mechanism into previous step supervisory controllers for adaptive fuzzy control is proposed to relax bounds required in the control process. In traditional supervisory adaptive fuzzy control approaches, the use of fuzzy estimators for approximating system functions and a robust supervisory control law are necessary to deal with any possi...
متن کاملRobust Adaptive Fuzzy Sliding Mode Control of Permanent Magnet Stepper Motor with Unknown Parameters and Load Torque
In this paper, robust adaptive fuzzy sliding mode control is designed to control the Permanent Magnet (PM) stepper motor in the presence of model uncertainties and disturbances. In doing so, the nonlinear model is converted to canonical form, then, for designing the controller, the robust sliding mode control is designed to decrease the effects of uncertainties and disturbances. A class of fuzz...
متن کاملDirect Adaptive Fuzzy-neural Control With State Observer & Supervisory Controller for Unknown Nonlinear Dynamical Systems
In this paper, an observer-based direct adaptive fuzzy-neural network (FNN) controller with supervisory mode for a certain class of high order unknown nonlinear dynamical system is presented. The direct adaptive control (DAC) has the advantage of less design effort by not using FNN to model the plant. By using an observer-based output feedback control law and adaptive law, the free parameters o...
متن کاملAn Adaptive Sliding Surface Slope Adjustment in Sliding Mode Fuzzy Control Techniques for Brushless DC Motor Drives
This paper presents the development and performance analysis of intelligent control techniques such as Sliding Mode controller and Fuzzy logic Controller for Brushless DC (BLDC)motor drives. Today, strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance. One of the best nonlinear robust controller which can be used i...
متن کاملSupervisory Adaptive Network-Based Fuzzy Inference System (SANFIS) Design for Empirical Test of Mobile Robot
A supervisory Adaptive Network‐based Fuzzy Inference System (SANFIS) is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off‐line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error bet...
متن کامل