Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two config...

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Main Author: Ahmed Sabah Abdul Ameer Al-Araji
Format: Article
Language:English
Published: Al-Khwarizmi College of Engineering – University of Baghdad 2017-09-01
Series:Al-Khawarizmi Engineering Journal
Subjects:
Online Access:http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/16
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author Ahmed Sabah Abdul Ameer Al-Araji
author_facet Ahmed Sabah Abdul Ameer Al-Araji
author_sort Ahmed Sabah Abdul Ameer Al-Araji
collection DOAJ
description In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearity
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spelling doaj.art-fcbbccbadb5544f4b17cf5a1bd2cb7a12022-12-21T23:08:37ZengAl-Khwarizmi College of Engineering – University of BaghdadAl-Khawarizmi Engineering Journal1818-11712312-07892017-09-0111Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical SystemsAhmed Sabah Abdul Ameer Al-Araji0University of TechnologyIn this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearityhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/16Self-Tuning --- Neuro Network --- Adaptive Controller.
spellingShingle Ahmed Sabah Abdul Ameer Al-Araji
Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
Al-Khawarizmi Engineering Journal
Self-Tuning --- Neuro Network --- Adaptive Controller.
title Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
title_full Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
title_fullStr Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
title_full_unstemmed Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
title_short Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
title_sort neuro self tuning adaptive controller for non linear dynamical systems
topic Self-Tuning --- Neuro Network --- Adaptive Controller.
url http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/16
work_keys_str_mv AT ahmedsabahabdulameeralaraji neuroselftuningadaptivecontrollerfornonlineardynamicalsystems