Yu, Xiang, Fu, Yu, Li, Peng and Zhang, Youmin (2017) Fault-Tolerant Aircraft Control Based on Self-Constructing Fuzzy Neural Networks and Multivariable SMC under Actuator Faults. IEEE Transactions on Fuzzy Systems . pp. 1-11. ISSN 1063-6706 (In Press)
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Official URL: http://dx.doi.org/10.1109/TFUZZ.2017.2773422
Abstract
This paper presents a fault-tolerant aircraft control (FTAC) scheme against actuator faults. Firstly, the upper bounds of the norms of the unknown functions are introduced, which contain actuator faults and model uncertainties. Subsequently, self-constructing fuzzy neural networks (SCFNNs) with adaptive laws are capable of obtaining the bounds. The bound estimation can reduce the computational burden with a lower amount of rules and weights, rather than the dynamic matrix approximation. Moreover, with the aid of SCFNNs, a multivariable sliding mode control (SMC) is developed to guarantee the finite-time stability of the handicapped aircraft. As compared to the existing intelligent FTAC techniques, the proposed method has twofold merits: fault accommodation can be promptly accomplished and decoupled difficulties can be overcome. Finally, simulation results from the nonlinear longitudinal Boeing 747 aircraft model illustrate the capability of the presented FTAC scheme.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering |
|---|---|
| Item Type: | Article |
| Refereed: | Yes |
| Authors: | Yu, Xiang and Fu, Yu and Li, Peng and Zhang, Youmin |
| Journal or Publication: | IEEE Transactions on Fuzzy Systems |
| Date: | 13 November 2017 |
| Funders: |
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| Digital Object Identifier (DOI): | 10.1109/TFUZZ.2017.2773422 |
| Keywords: | Fault-tolerant aircraft control, actuator faults, self-constructing fuzzy neural network, finite-time stability, multivariable sliding mode control |
| ID Code: | 983244 |
| Deposited By: | Danielle Dennie |
| Deposited On: | 28 Nov 2017 13:48 |
| Last Modified: | 18 Jan 2018 17:56 |
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