TY - GEN
T1 - Multidisciplinary and Multi-objective Design Optimization for Unmanned Aerial Vehicle System
AU - Liu, Zhenyu
AU - Long, Teng
AU - Jiao, Yingjie
AU - Shi, Renhe
AU - Ye, Nian Hui
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - In modern wars, unmanned aerial vehicle (UAV) swarm has been developed for cooperative engagements. To further improve the UAV swarm combat effectiveness, it is necessary to apply multidisciplinary design optimization (MDO) for UAV system design considering the mission scenario. Based on the characteristics of UAVs, the UAV multidisciplinary analysis models are constructed including flight range, penetration, search, strike, and cost disciplines. The MDO problem is then formulated to maximize the effectiveness indexes (i.e., mission completion probability and flight range) and minimize the expenditure indexes (i.e., take-off weight and cost) simultaneously. Additionally, a surrogate-based multi-objective optimization method is utilized to solve the studied UAV MDO problem efficiently. Compared with the initial design, the optimized solution can save the cost and increase the flight range simultaneously, which demonstrates the effectiveness and practicality of the UAV multidisciplinary optimization work in this paper.
AB - In modern wars, unmanned aerial vehicle (UAV) swarm has been developed for cooperative engagements. To further improve the UAV swarm combat effectiveness, it is necessary to apply multidisciplinary design optimization (MDO) for UAV system design considering the mission scenario. Based on the characteristics of UAVs, the UAV multidisciplinary analysis models are constructed including flight range, penetration, search, strike, and cost disciplines. The MDO problem is then formulated to maximize the effectiveness indexes (i.e., mission completion probability and flight range) and minimize the expenditure indexes (i.e., take-off weight and cost) simultaneously. Additionally, a surrogate-based multi-objective optimization method is utilized to solve the studied UAV MDO problem efficiently. Compared with the initial design, the optimized solution can save the cost and increase the flight range simultaneously, which demonstrates the effectiveness and practicality of the UAV multidisciplinary optimization work in this paper.
KW - Multi-objective optimization
KW - Multidisciplinary analysis model
KW - Multidisciplinary design optimization
KW - Surrogate-based optimization
KW - Unmanned aerial vehicles
UR - http://www.scopus.com/inward/record.url?scp=85130921814&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-9492-9_255
DO - 10.1007/978-981-16-9492-9_255
M3 - Conference contribution
AN - SCOPUS:85130921814
SN - 9789811694912
T3 - Lecture Notes in Electrical Engineering
SP - 2594
EP - 2605
BT - Proceedings of 2021 International Conference on Autonomous Unmanned Systems, ICAUS 2021
A2 - Wu, Meiping
A2 - Niu, Yifeng
A2 - Gu, Mancang
A2 - Cheng, Jin
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Autonomous Unmanned Systems, ICAUS 2021
Y2 - 24 September 2021 through 26 September 2021
ER -