Open Access
ARTICLE
A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability
1 College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China
2 Beijing Special Engineering Design Institution, Beijing, 100028, China
* Corresponding Author: Ping Jiang. Email:
(This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Computer Modeling in Engineering & Sciences 2024, 140(2), 1889-1918. https://doi.org/10.32604/cmes.2024.049813
Received 18 January 2024; Accepted 01 April 2024; Issue published 20 May 2024
Abstract
The unmanned aerial vehicle (UAV) swarm plays an increasingly important role in the modern battlefield, and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm. Due to the high cost and long duration of operational tests, it is essential to plan the test in advance. To solve the problem of planning UAV swarm operational test, this study considers the multi-stage feature of a UAV swarm mission, composed of launch, flight and combat stages, and proposes a method to find test plans that can maximize mission reliability. Therefore, a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission. A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans. This study first constructs a mission reliability model for the UAV swarm in the combat stage. Then, the launch stage and flight stage are integrated to develop a complete PMS (Phased Mission Systems) reliability model. Finally, the Binary Decision Diagrams (BDD) and Multi Objective Quantum Particle Swarm Optimization (MOQPSO) methods are proposed to solve the model. The optimal plans considering both reliability and cost are obtained. The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.Keywords
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