Multiple UAVs Networking Oriented Consistent Cooperation Method Based on Adaptive Arithmetic Sine Cosine Optimization

Abstract

With the rapid development of the Internet of Things, the Internet of Vehicles (IoV) has quickly drawn considerable attention from the public. The cooperative unmanned aerial vehicles (UAVs)-assisted vehicular networks, as a part of IoV, has become an emerging research spot. Due to the significant limitations of the application and service of a single UAV-assisted vehicular networks, efforts have been put into studying the use of multiple UAVs to assist effective vehicular networks. However, simply increasing the number of UAVs can lead to difficulties in information exchange and collisions caused by external interference, thereby affecting the security of the entire cooperation and networking. To address the above problems, multiple UAV cooperative formation is increasingly receiving attention. UAV cooperative formation can not only save energy loss but also achieve synchronous cooperative motion through information communication between UAVs, prevent collisions and other problems between UAVs, and improve task execution efficiency. A multi-UAVs cooperation method based on arithmetic optimization is proposed in this work. Firstly, a complete mechanical model of unmanned maneuvering was obtained by combining acceleration limitations. Secondly, based on the arithmetic sine and cosine optimization algorithm, the mathematical optimizer was used to accelerate the function transfer. Sine and cosine strategies were introduced to achieve a global search and enhance local optimization capabilities. Finally, in obtaining the precise position and direction of multi-UAVs to assist networking, the cooperation method was formed by designing the reference controller through the consistency algorithm. Experimental studies were carried out for the multi-UAVs’ cooperation with the particle model, combined with the quadratic programming problem-solving technique. The results show that the proposed quadrotor dynamic model provides basic data for cooperation position adjusting, and our simplification in the model can reduce the amount of calculations for the feedback and the parameter changes during the cooperation. Moreover, combined with a reference controller, the UAVs achieve the predetermined cooperation by offering improved navigation speed, task execution efficiency, and cooperation accuracy. Our proposed multi-UAVs cooperation method can improve the quality of service significantly on the UAV-assisted vehicular networks.