Intelligent finite-time formation control for flapping wing micro aerial vehicles
This paper investigates the intelligent finite time formation control for multiple Flapping wing micro aerial vehicles (FWMAVs) system. Firstly, the translational and the rotational attitude motion equations are proposed based on the Lagrangian equation for FWMAVs. The motion system is decouple into...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-10-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023081525 |
| _version_ | 1827780264904884224 |
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| author | Xiaoyan He Zhaojing Yang Linke Zhang Chun Zha |
| author_facet | Xiaoyan He Zhaojing Yang Linke Zhang Chun Zha |
| author_sort | Xiaoyan He |
| collection | DOAJ |
| description | This paper investigates the intelligent finite time formation control for multiple Flapping wing micro aerial vehicles (FWMAVs) system. Firstly, the translational and the rotational attitude motion equations are proposed based on the Lagrangian equation for FWMAVs. The motion system is decouple into an internal and an external dual loop subsystems. An adaptive neural network estimation algorithm is proposed based on the internal and external double loop system of the coupled model to effectively estimate the uncertainties and the external disturbances of the model. In addition, two effective intelligent control protocols are presented for the translational and the rotational attitude motion subsystem, respectively, by utilizing potential energy function, generalized inverse matrix, and finite-time stability. The main contribution of this paper is the case that, four control objectives are achieved for multiple FWMAVs system, including the estimation of uncertainties, collision avoidance, connectivity preservation, and finite time convergence. Finally, a simulation example of formation tracking control is given by using matlab software in the numerical simulation part, and the effectiveness of the obtained results and the superiority of the control protocol are verified. |
| first_indexed | 2024-03-11T15:02:16Z |
| format | Article |
| id | doaj.art-ec07f8839873441196740ab80e84c603 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-11T15:02:16Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ec07f8839873441196740ab80e84c6032023-10-30T06:07:55ZengElsevierHeliyon2405-84402023-10-01910e20944Intelligent finite-time formation control for flapping wing micro aerial vehiclesXiaoyan He0Zhaojing Yang1Linke Zhang2Chun Zha3Corresponding author.; School of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Huhhot, 010070, ChinaSchool of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Huhhot, 010070, ChinaSchool of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Huhhot, 010070, ChinaSchool of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Huhhot, 010070, ChinaThis paper investigates the intelligent finite time formation control for multiple Flapping wing micro aerial vehicles (FWMAVs) system. Firstly, the translational and the rotational attitude motion equations are proposed based on the Lagrangian equation for FWMAVs. The motion system is decouple into an internal and an external dual loop subsystems. An adaptive neural network estimation algorithm is proposed based on the internal and external double loop system of the coupled model to effectively estimate the uncertainties and the external disturbances of the model. In addition, two effective intelligent control protocols are presented for the translational and the rotational attitude motion subsystem, respectively, by utilizing potential energy function, generalized inverse matrix, and finite-time stability. The main contribution of this paper is the case that, four control objectives are achieved for multiple FWMAVs system, including the estimation of uncertainties, collision avoidance, connectivity preservation, and finite time convergence. Finally, a simulation example of formation tracking control is given by using matlab software in the numerical simulation part, and the effectiveness of the obtained results and the superiority of the control protocol are verified.http://www.sciencedirect.com/science/article/pii/S2405844023081525Flapping wing micro aerial vehiclesFinite-time formation controlNeural networksInternal and external circulationConnectivity preservation |
| spellingShingle | Xiaoyan He Zhaojing Yang Linke Zhang Chun Zha Intelligent finite-time formation control for flapping wing micro aerial vehicles Heliyon Flapping wing micro aerial vehicles Finite-time formation control Neural networks Internal and external circulation Connectivity preservation |
| title | Intelligent finite-time formation control for flapping wing micro aerial vehicles |
| title_full | Intelligent finite-time formation control for flapping wing micro aerial vehicles |
| title_fullStr | Intelligent finite-time formation control for flapping wing micro aerial vehicles |
| title_full_unstemmed | Intelligent finite-time formation control for flapping wing micro aerial vehicles |
| title_short | Intelligent finite-time formation control for flapping wing micro aerial vehicles |
| title_sort | intelligent finite time formation control for flapping wing micro aerial vehicles |
| topic | Flapping wing micro aerial vehicles Finite-time formation control Neural networks Internal and external circulation Connectivity preservation |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023081525 |
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