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An adaptive predictive control based on a quasi-ARX neural network model

A quasi-ARX (quasi-linear ARX) neural network (QARXNN) model is able to demonstrate its ability for identification and prediction highly nonlinear system. The model is simplified by a linear correlation between the input vector and its nonlinear coefficients. The coefficients are used to parameter...

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Main Authors: Abu Jami’in, Mohammad, Sutrisno, Imam, Hu, Jinglu, Mariun, Norman, Marhaban, Mohammad Hamiruce
Format: Conference or Workshop Item
Published: IEEE 2014
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id oai:psasir.upm.edu.my:41438
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spelling oai:psasir.upm.edu.my:41438 http://psasir.upm.edu.my/id/eprint/41438/ An adaptive predictive control based on a quasi-ARX neural network model Abu Jami’in, Mohammad Sutrisno, Imam Hu, Jinglu Mariun, Norman Marhaban, Mohammad Hamiruce A quasi-ARX (quasi-linear ARX) neural network (QARXNN) model is able to demonstrate its ability for identification and prediction highly nonlinear system. The model is simplified by a linear correlation between the input vector and its nonlinear coefficients. The coefficients are used to parameterize the input vector performed by an embedded system called as state dependent parameter estimation (SDPE), which is executed by multi layer parceptron neural network (MLPNN). SDPE consists of the linear and nonlinear parts. The controller law is derived via SDPE of the linear and nonlinear parts through switching mechanism. The dynamic tracking controller error is derived then the stability analysis of the closed-loop controller is performed based Lyapunov theorem. Linear based adaptive robust control and nonlinear based adaptive robust control is performed with the switching of the linear and nonlinear parts parameters based Lyapunov theorem to guarantee bounded and convergence error. IEEE 2014 Conference or Workshop Item NonPeerReviewed Abu Jami’in, Mohammad and Sutrisno, Imam and Hu, Jinglu and Mariun, Norman and Marhaban, Mohammad Hamiruce (2014) An adaptive predictive control based on a quasi-ARX neural network model. In: 13th International Conference on Control Automation Robotics & Vision (ICARCV 2014), 10-12 Dec. 2014 , Marina Bay Sands, Singapore. (pp. 253-258). 10.1109/ICARCV.2014.7064314
institution UPM IR
collection UPM IR
description A quasi-ARX (quasi-linear ARX) neural network (QARXNN) model is able to demonstrate its ability for identification and prediction highly nonlinear system. The model is simplified by a linear correlation between the input vector and its nonlinear coefficients. The coefficients are used to parameterize the input vector performed by an embedded system called as state dependent parameter estimation (SDPE), which is executed by multi layer parceptron neural network (MLPNN). SDPE consists of the linear and nonlinear parts. The controller law is derived via SDPE of the linear and nonlinear parts through switching mechanism. The dynamic tracking controller error is derived then the stability analysis of the closed-loop controller is performed based Lyapunov theorem. Linear based adaptive robust control and nonlinear based adaptive robust control is performed with the switching of the linear and nonlinear parts parameters based Lyapunov theorem to guarantee bounded and convergence error.
format Conference or Workshop Item
author Abu Jami’in, Mohammad
Sutrisno, Imam
Hu, Jinglu
Mariun, Norman
Marhaban, Mohammad Hamiruce
spellingShingle Abu Jami’in, Mohammad
Sutrisno, Imam
Hu, Jinglu
Mariun, Norman
Marhaban, Mohammad Hamiruce
An adaptive predictive control based on a quasi-ARX neural network model
author_facet Abu Jami’in, Mohammad
Sutrisno, Imam
Hu, Jinglu
Mariun, Norman
Marhaban, Mohammad Hamiruce
author_sort Abu Jami’in, Mohammad
title An adaptive predictive control based on a quasi-ARX neural network model
title_short An adaptive predictive control based on a quasi-ARX neural network model
title_full An adaptive predictive control based on a quasi-ARX neural network model
title_fullStr An adaptive predictive control based on a quasi-ARX neural network model
title_full_unstemmed An adaptive predictive control based on a quasi-ARX neural network model
title_sort adaptive predictive control based on a quasi-arx neural network model
publisher IEEE
publishDate 2014
_version_ 1819296362151280640
score 13.4562235

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