Chaos grey wolf optimization-based unmanned aerial vehicle formation control method

A control method and technology of unmanned aerial vehicle, applied in the direction of chaos model, adaptive control, general control system, etc., can solve the problems of limited application space and large amount of calculation.

Active Publication Date: 2020-07-24
BEIHANG UNIV
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However, due to the limitations of the model predictive control itself, for the online solution of constrained optimizatio...

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  • Chaos grey wolf optimization-based unmanned aerial vehicle formation control method
  • Chaos grey wolf optimization-based unmanned aerial vehicle formation control method
  • Chaos grey wolf optimization-based unmanned aerial vehicle formation control method

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[0098] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0099] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

[0100] The invention solves the problem of UAV formation control, and proposes a distributed model prediction framework based on chaotic gray wolf optimization for UAV formation control. Compared with...

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Abstract

The invention proposes a chaos grey wolf optimization-based unmanned aerial vehicle formation control method. A distributed model predictive control (MPC) frame of unmanned aerial vehicle formation control is built, each unmanned aerial vehicle only shares information with a neighbor, and the communication requirement and the computational complexity are reduced; a chaos optimization algorithm iscombined with a grey wolf optimization algorithm, and thus, the algorithm performance is improved; and the algorithm is combined with the distributed MPC, finite horizon optimal control problem (FHOCP) is solved, so that unmanned aerial vehicle formation control is achieved.

Description

technical field [0001] The invention belongs to the technical field of coordinated control of unmanned aerial vehicles, and in particular relates to an unmanned aerial vehicle formation control method based on chaotic gray wolf optimization. Background technique [0002] Unmanned Aerial Vehicle (UAV) has various applications in military and civilian fields, such as reconnaissance, surveillance, precision agriculture, cargo transportation, and forest firefighting. At present, the trend of "unmanned" is increasingly reflected in warfare, and the development momentum of UAV technology is getting better and better. Compared with a single UAV, multi-UAV formations have "self-healing" capabilities, environmental High adaptability and strong task execution. Multi-UAV systems have better performance in complex tasks. For example, in reconnaissance, UAV formations are conducive to the establishment of three-dimensional battlefield models; in air combat, cooperative operations can be...

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Application Information

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IPC IPC(8): G05D1/10G05B13/04G06N3/00G06N7/08
CPCG05B13/042G05D1/104G06N3/006G06N7/08
Inventor 吴坤张田蔡志浩赵江王英勋
Owner BEIHANG UNIV
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