Multi-UAV simultaneous-arrival collaborative control method

Abstract

The invention relates to a multi-UAV simultaneous-arrival collaborative control method and belongs to the technical field of flight test, UAVs (unmanned aerial vehicle) and collaborative control. Themethod comprises a decentralized control structure relying only on local information interaction and a decentralized control strategy based on a consistency algorithm. The two are combined according to different features of path planning and speed control, and complementary advantages thereof are utilized to cope with influence of adverse factors of path errors and emergent threats and the like. The method realizes simultaneous arrival of multiple UAVs, thereby improving flexibility, robustness, and reliability of the control strategy, improving multi-UAV cooperative combat efficiency and enabling a multi-UAV combat large-scale system to play a greater role in the war.

Description

technical field [0001] The invention relates to a multi-UAV simultaneous arrival cooperative control method, which belongs to the technical field of flight test, UAV and cooperative control. Background technique [0002] The two main features of current UCAV collaborative mission control research are: [0003] (1) Distributed control has become an important development direction and research hotspot [0004] The control methods of multi-UCAV systems are mainly divided into centralized control and distributed control. After long-term research and full development, centralized control has achieved a large number of research results. However, in recent years, with the rapid development of distributed control technology and its advantages in solving dynamic and uncertain problems, as well as the continuous improvement of UCAV autonomy Under the trend of UCAV, distributed control has gradually become an important development direction and research hotspot of multi-UCAV cooperat...

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Problems solved by technology

[0011] (2) Solving the multi-UCAV task assignment problem

Under the condition that the problem has a solution, the optimization method can guarantee the optimal solution of the problem based on some simplified assumptions, but as the scale of the problem increases, the difficulty of solving it also increases sharply, and the time consumption increases exponentially

Another shortcoming of this type of method is that the ability to describe complex problems is limited, the established model cannot fully reflect the complexity of the battlefield environment, and it is extremely difficult to express the randomness and dynamics of the battlefield environment

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