Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched...

متن کامل

ADAPTIVE FUZZY TRACKING CONTROL FOR A CLASS OF NONLINEAR SYSTEMS WITH UNKNOWN DISTRIBUTED TIME-VARYING DELAYS AND UNKNOWN CONTROL DIRECTIONS

In this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.Based on the backstepping technique, the adaptive fuzzy controller is constructed. The main contributions of the paper...

متن کامل

Adaptive Neural Network-Based Predictive Control for Nonlinear Dynamical Systems

In the paper, we propose a predictive control scheme using a neural network-based prediction model for nonlinear processes. To identify the system dynamics, we approximate the nonlinear function with an affine function of some of its arguments and construct a special type of prediction model using three-layered feedforward neural networks. Using some available inputoutput data pairs of the plan...

متن کامل

Online Neural Network Adaptive Control of a Class of Nonlinear Systems Using Fuzzy Inference Reasoning

This study addresses the proposition of neural network (NN) adaptive control for a class of nonlinear systems using fuzzy reasoning. In first step, an ideal control law is established based on feedback linearization technique and certainty equivalence. Then the NN system is introduced on line to approximate this ideal control law. The parameters of the NN system are on-line adapted and changed ...

متن کامل

Recurrent Fuzzy Neural Network Control for Mimo Nonlinear Systems

This paper develops a design method of recurrent fuzzy neural network (RFNN) control system for multi-input multi-output (MIMO) nonlinear dynamic systems. This control system consists of a state feedback controller and an RFNN controller. The state feedback controller is a basic stabilizing controller to stabilize the system, and the RFNN controller presents a robust controller to deal with unc...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Intelligence and Neuroscience

سال: 2015

ISSN: 1687-5265,1687-5273

DOI: 10.1155/2015/719620