DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Tahk, Min-Jea | - |
dc.contributor.advisor | 탁민제 | - |
dc.contributor.author | Yoo, Dong-Wan | - |
dc.contributor.author | 유동완 | - |
dc.date.accessioned | 2015-04-23T02:06:53Z | - |
dc.date.available | 2015-04-23T02:06:53Z | - |
dc.date.issued | 2014 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=591864&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/196195 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 항공우주공학전공, 2014.8, [ ix, 96p. ] | - |
dc.description.abstract | In this research, an optimal distribution algorithm for a large group of heterogeneous un-manned aerial vehicles (UAVs) is developed. A typical UAV cooperative mission in a battlefield can be categorized as a hierarchical system that is usually composed of several levels, and the decision making step is the main focus of this paper. In the decision making step, the factors to be decided are the proper number and types of UAVs that will be committed to each operational area to enhance the overall performance of the entire group and achieve a successful mission accomplishment. A task assignment algorithm, which is the next level in the cooperative control hierarchy, may begin with a higher chance of success when the number and type of resources are optimally given by the preceding decision making step. To aid the decision making process in SEAD missions, a number of high fidelity deterministic models that well emulate SEAD situation is derived and formulated to compose integer linear programming (ILP) problems. Three SEAD deterministic models (SDM) are defined and derived to maximize the number of survived strikers at the end of the mission, and to minimize the total missions time, or combination of the two. Three performance indices are applied to formulate ILP problems whose solutions give the optimal combinations of UAVs for SEAD missions. Also, refined SEAD deterministic models (SDMs) are applied to formulate mixed integer nonlinear programming (MINLP) problems, which are subject to several nonlinear constraints. Solving MINLP problems by co-evolutionary augmented Lagrangian method (CEALM), optimal quantity and type of UAVs are obtained to successfully decide the required initial war assets for the completion of the SEAD mission. Given quantities of groups of UAVs are optimally allocated using the resource allocation algorithms with different types of objectives depending on the current war situation. To analyze the final allocation results, two solution han... | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Decision Making | - |
dc.subject | 비선형 계획법 | - |
dc.subject | 정수형 선형 계획법 | - |
dc.subject | 적 방공망 제압 | - |
dc.subject | 자원 분배 | - |
dc.subject | 협업 제어 | - |
dc.subject | UAV | - |
dc.subject | Resource Allocation | - |
dc.subject | Cooperative Controls | - |
dc.subject | Suppression of Enemy Air Defense (SEAD) | - |
dc.subject | ILP | - |
dc.subject | MINLP | - |
dc.subject | 무인항공기 | - |
dc.subject | 의사 결정 | - |
dc.title | Optimal resource allocation algorithms for uav suppression of enemy air defense missions | - |
dc.title.alternative | 무인 항공기의 적 방공망 제압 임무를 위한 최적 자원 분배 알고리즘 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 591864/325007 | - |
dc.description.department | 한국과학기술원 : 항공우주공학전공, | - |
dc.identifier.uid | 020115179 | - |
dc.contributor.localauthor | Tahk, Min-Jea | - |
dc.contributor.localauthor | 탁민제 | - |
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