Formulation of control strategies for requirement definition of multi-agent surveillance systems
Başlık çevirisi mevcut değil.
- Tez No: 403425
- Danışmanlar: Prof. DIMITRI N. MAVRIS
- Tez Türü: Doktora
- Konular: Astronomi ve Uzay Bilimleri, Astronomy and Space Sciences
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2014
- Dil: İngilizce
- Üniversite: Georgıa Instıtute Of Technology
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
Özet yok.
Özet (Çeviri)
Over the last decade, advances in networking and computing technologies, along with new manufacturing techniques, have enabled a new paradigm shift towards multiagent systems in engineering applications. This shift has facilitated a significant interest in the design and the control of such systems. Examples of multi-agent systems include, but are not limited to, a swarm of mobile robots, wireless sensor networks, satellite constellations, or a group of unmanned aerial vehicles (UAVs). In a multi-agent system (MAS), the overall performance is greatly influenced by both the design and the control of the agents. The physical design determines the agent capabilities, and the control strategies drive the agents to pursue their objectives using the available capabilities. For example, in a multi-agent surveillance mission, the endurance of an agent is the amount of time it can operate in the mission area without refueling. On the other hand, an energy-aware control strategy enables the agents to efficiently use their limited fuel when monitoring the surveillance area. In this respect, how frequently an agent leaves the mission area for refueling (i.e. causing a degradation in the situational awareness) depends on both the endurance of the agent and the energy efficiency of the control strategy. The objective of this thesis is to incorporate control strategies in the early conceptual design of an MAS. As such, this thesis proposes an additional component introduced to a generic design methodology of MAS, and it mainly explores the interdependency between the design variables of the agents and the control strategies used by the agents. The proposed methodology consists of two modules. In the control module, a set of candidate control strategies is generated based on the mission specifications. In the design module, the influential design variables are identified for each candidate strategy through a design space exploration. Accordingly, the output of the proposed methodology, i.e. the interdependency between the design variables and the control strategies, can be utilized in the later design stages to optimize the overall system through some higher fidelity analyses. In this thesis, the proposed methodology is applied to a persistent multi-UAV surveillance problem. The main objective of this problem is to increase the situational awareness of a base that receives some instantaneous monitoring information from a group of UAVs. Each UAV has a limited energy capacity and a limited communication range. Accordingly, the connectivity of the communication network becomes essential for the information flow from the UAVs to the base. However, in long-run missions, the UAVs need to return to the base for refueling/recharging with certain frequencies depending on their endurance. Whenever a UAV leaves the surveillance area, the remaining UAVs may need relocation to mitigate the impact of its absence. Accordingly, the proposed methodology is applied to this problem as follows: In the control module of the proposed methodology, a set of energy-aware control strategies are developed for efficient multi-UAV surveillance operations. To this end, this thesis first proposes a decentralized strategy to recover the connectivity of the communication network, which maintains the instantaneous information flow from the UAVs to the base. Second, it presents two return policies for UAVs to achieve energy-aware persistent surveillance. In the design module of the proposed methodology, a design space exploration is performed to investigate the overall performance by varying a set of design variables and the candidate control strategies developed in the control module. Overall, it is shown that a control strategy used by an MAS affects the influence of the design variables (i.e. physical characteristics) on the mission performance. Furthermore, the proposed methodology identifies the preferable pairs of design variables and control strategies through low fidelity analysis in the early design stages.
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