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Design of Sliding Mode - Neural Network Controller with Fuzzy Observer for Hyper Chaotic Systems Considering Uncertainty, Disturbance, and Nonlinear Control Inputs

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Type: Conference paper
Language: English
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TEDECE01_664

Index date: 21 November 2015

Design of Sliding Mode - Neural Network Controller with Fuzzy Observer for Hyper Chaotic Systems Considering Uncertainty, Disturbance, and Nonlinear Control Inputs abstract

The main idea of chaos is defining behavior of certain systems that are highly sensitive to their initial condition. In chaotic systems, using a nonlinear controller is recommended to achieve good performance. Sliding mode controller is a robust state feedback controller to deal with uncertainties and has fast transient response. However, it is not an appropriate controller in the steady state of the system because of the existence of chattering. On the other hand, the neural controller is successfully applied on the control of chaotic systems but transient performance of this controller is not appropriate in the face of uncertainties due to its inevitable learning process In this paper, a hybrid sliding mode-neural network controller with variable weights is designed to utilize the advantages of both controllers. A fuzzy observer has the task of optimal tuning of these coefficients. The fuzzy observer also supervises the switching process between the two controllers.

Design of Sliding Mode - Neural Network Controller with Fuzzy Observer for Hyper Chaotic Systems Considering Uncertainty, Disturbance, and Nonlinear Control Inputs Keywords:

Design of Sliding Mode - Neural Network Controller with Fuzzy Observer for Hyper Chaotic Systems Considering Uncertainty, Disturbance, and Nonlinear Control Inputs authors

Mahsa Haghani

Department of Electrical Eng., Faculty of Eng Islamic Azad University. Tehran

Abbas Ghanbari

Department of Electrical Eng., Faculty of Eng Islamic Azad University. Tehran

Mahmood Mola

Department of Electrical Eng., Faculty of Eng Islamic Azad University. Tehran

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