The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 53-189
Full Name: PRAKASH1 RAGU
Position: Assistant Professor
Age: ON
Sex: Male
Address: Department of Electrical and Electronics Engineering
Country: INDIA
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E-mail address: prakashragu@yahoo.co.in
Other E-mails: prakashraguu@gmail.com
Title of the Paper: A New Approach to Model Reference Adaptive Control for Nonlinear Systems using Neural Network Controller
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Number of paper pages: 10
Abstract: The aim of this paper is to design "a neural network based intelligent model reference adaptive controller". In this scheme, the intelligent supervisory loop is incorporated into the conventional model reference adaptive controller framework by utilizing an online growing multilayer back propagation neural network structure in parallel with it. The idea is to control the plant by conventional model reference adaptive controller with a suitable single reference model, and at the same time respond to plant by online tuning of a multilayer Back Propagation neural controller. The training patterns for the neuron controller are obtained from the conventional PI controller and the effectiveness of the proposed neuron controller is studied using simulation studies. The artificial neural network has the ability to generalize and can interpolate in between the training data. The parallel neural controller is designed in order to precisely track the system output to the desi!
red command trajectory. The proposed neural network based controller can significantly improve system behavior and force the system to follow the reference model and minimize the error between the model and plant output. The effectiveness of the proposal control scheme is demonstrated by simulation. The proposed "neural network based intelligent model reference adaptive controller" designed was tested on two different plants and found to work effectively on driving both of them.
Keywords: Model Reference Adaptive Controller (MRAC), Artificial Neural Network (ANN), PI controller.Dead Zone,Backlash
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