Neural networks-based robust adaptive flight path tracking control of large transport
For the ultralow altitude airdrop decline stage, many factors such as actuator nonlinearity, the uncertain atmospheric disturbances, and model unknown nonlinearity affect the precision of trajectory tracking. A robust adaptive neural network dynamic surface control method is proposed. The neural net...
| Permalink: | http://skupnikatalog.nsk.hr/Record/nsk.NSK01001046202/Details |
|---|---|
| Matična publikacija: |
Engineering review (Online) 38 (2018), 3 ; str. 268-278 |
| Glavni autori: | Lv, Maolong (Author), Sun, Xiuxia, Xu, G. Z., Wang, Z. T. |
| Vrsta građe: | e-članak |
| Jezik: | eng |
| Predmet: | |
| Online pristup: |
https://doi.org/10.30765/er.38.3.3 Hrčak |
| LEADER | 02021naa a22003854i 4500 | ||
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| 008 | 191108s2018 ci a |o |0|| ||eng | ||
| 024 | 7 | |2 doi |a 10.30765/er.38.3.3 | |
| 035 | |a (HR-ZaNSK)001046202 | ||
| 040 | |a HR-ZaNSK |b hrv |c HR-ZaNSK |e ppiak | ||
| 041 | 0 | |a eng |b eng | |
| 042 | |a croatica | ||
| 044 | |a ci |c hr | ||
| 080 | 1 | |a 656 |2 2011 | |
| 080 | 1 | |a 004 |2 2011 | |
| 100 | 1 | |a Lv, Maolong |4 aut |9 HR-ZaNSK | |
| 245 | 1 | 0 | |a Neural networks-based robust adaptive flight path tracking control of large transport |h [Elektronička građa] / |c Maolong Lv, Xiuxia Sun, G. Z. Xu, Z. T. Wang. |
| 300 | |b Ilustr. | ||
| 504 | |a Bibliografija: 26 jed. | ||
| 504 | |a Abstract. | ||
| 520 | |a For the ultralow altitude airdrop decline stage, many factors such as actuator nonlinearity, the uncertain atmospheric disturbances, and model unknown nonlinearity affect the precision of trajectory tracking. A robust adaptive neural network dynamic surface control method is proposed. The neural network is used to approximate unknown nonlinear continuous functions of the model, and a nonlinear robust term is introduced to eliminate the actuator’s nonlinear modeling error and external disturbances. From Lyapunov stability theorem, it is rigorously proved that all the signals in the closed-loop system are bounded. Simulation results confirm the perfect tracking performance and strong robustness of the proposed method. | ||
| 653 | 0 | |a Neuronske mreže |a Dinamička kontrola |a Zračni promet |a Kut upravljanja | |
| 700 | 1 | |a Sun, Xiuxia |4 aut |9 HR-ZaNSK | |
| 700 | 1 | |a Xu, G. Z. |4 aut |9 HR-ZaNSK | |
| 700 | 1 | |a Wang, Z. T. |4 aut |9 HR-ZaNSK | |
| 773 | 0 | |t Engineering review (Online) |x 1849-0433 |g 38 (2018), 3 ; str. 268-278 |w nsk.(HR-ZaNSK)000848891 | |
| 981 | |b Be2018 |b B02/18 | ||
| 998 | |b tino1911 | ||
| 856 | 4 | 0 | |u https://doi.org/10.30765/er.38.3.3 |
| 856 | 4 | 1 | |y Digitalna.nsk.hr |
| 856 | 4 | 0 | |u https://hrcak.srce.hr/201150 |y Hrčak |