Abstract
This paper proposes a radial basis function neural network adaptive backstepping controller (RBFNN-ABC) for multiple-input multiple-output (MIMO) nonlinear systems in block-triangular form. The control scheme incorporates the adaptive neural backstepping design technique with a first-order filter at each step of the backstepping design to avoid the higher-order derivative problem, which is generated by the backstepping design. This problem may create an unpredictable and unfavorable influence on control performance because higher-order derivative term errors are introduced into the neural approximation model. Finally, simulation results demonstrate that the output tracking error between the plant output and the desired reference can be made arbitrarily small.
| Original language | English |
|---|---|
| Title of host publication | Proceedings 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 |
| Pages | 4946-4951 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2009 |
| Event | 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 - San Antonio, TX, United States Duration: 2009 Oct 11 → 2009 Oct 14 |
Other
| Other | 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 |
|---|---|
| Country | United States |
| City | San Antonio, TX |
| Period | 09/10/11 → 09/10/14 |
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Keywords
- Adaptive
- Backstepping
- MIMO nonlinear systems
- Radial basis function (RBF) neural networks (NNs)
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction
Cite this
RBF neural network adaptive backstepping controllers for MIMO nonaffine nonlinear systems. / Wang, Wei Yen; Hong, Chin Ming; Kuo, Ming Feng; Leu, Yih Guang; Lee, Tsu Tian.
Proceedings 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009. 2009. p. 4946-4951 5346245.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - RBF neural network adaptive backstepping controllers for MIMO nonaffine nonlinear systems
AU - Wang, Wei Yen
AU - Hong, Chin Ming
AU - Kuo, Ming Feng
AU - Leu, Yih Guang
AU - Lee, Tsu Tian
PY - 2009
Y1 - 2009
N2 - This paper proposes a radial basis function neural network adaptive backstepping controller (RBFNN-ABC) for multiple-input multiple-output (MIMO) nonlinear systems in block-triangular form. The control scheme incorporates the adaptive neural backstepping design technique with a first-order filter at each step of the backstepping design to avoid the higher-order derivative problem, which is generated by the backstepping design. This problem may create an unpredictable and unfavorable influence on control performance because higher-order derivative term errors are introduced into the neural approximation model. Finally, simulation results demonstrate that the output tracking error between the plant output and the desired reference can be made arbitrarily small.
AB - This paper proposes a radial basis function neural network adaptive backstepping controller (RBFNN-ABC) for multiple-input multiple-output (MIMO) nonlinear systems in block-triangular form. The control scheme incorporates the adaptive neural backstepping design technique with a first-order filter at each step of the backstepping design to avoid the higher-order derivative problem, which is generated by the backstepping design. This problem may create an unpredictable and unfavorable influence on control performance because higher-order derivative term errors are introduced into the neural approximation model. Finally, simulation results demonstrate that the output tracking error between the plant output and the desired reference can be made arbitrarily small.
KW - Adaptive
KW - Backstepping
KW - MIMO nonlinear systems
KW - Radial basis function (RBF) neural networks (NNs)
UR - http://www.scopus.com/inward/record.url?scp=74849105230&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74849105230&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2009.5346245
DO - 10.1109/ICSMC.2009.5346245
M3 - Conference contribution
AN - SCOPUS:74849105230
SN - 9781424427949
SP - 4946
EP - 4951
BT - Proceedings 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
ER -