A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks
Summary :
This paper presents a method of MRAC (model reference adaptive control) for MIMO (multi-input multi-output) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.8 pp.1933-1941
- Publication Date
- 2001/08/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Digital Signal Processing)
- Category
- Nonlinear Signal Processing
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Jianming LU, Jiunshian PHUAH, Takashi YAHAGI, "A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 8, pp. 1933-1941, August 2001, doi: .
Abstract: This paper presents a method of MRAC (model reference adaptive control) for MIMO (multi-input multi-output) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_8_1933/_p
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@ARTICLE{e84-a_8_1933,
author={Jianming LU, Jiunshian PHUAH, Takashi YAHAGI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks},
year={2001},
volume={E84-A},
number={8},
pages={1933-1941},
abstract={This paper presents a method of MRAC (model reference adaptive control) for MIMO (multi-input multi-output) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1933
EP - 1941
AU - Jianming LU
AU - Jiunshian PHUAH
AU - Takashi YAHAGI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2001
AB - This paper presents a method of MRAC (model reference adaptive control) for MIMO (multi-input multi-output) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.
ER -
English
