48 research outputs found
Differential Games For Multi-agent Systems Under Distributed Information
Get PDFIn this dissertation, we consider differential games for multi-agent systems under distributed information where every agent is only able to acquire information about the others according to a directed information graph of local communication/sensor networks. Such games arise naturally from many applications including mobile robot coordination, power system optimization, multiplayer pursuit-evasion games, etc. Since the admissible strategy of each agent has to conform to the information graph constraint, the conventional game strategy design approaches based upon Riccati equation(s) are not applicable because all the agents are required to have the information of the entire system. Accordingly, the game strategy design under distributed information is commonly known to be challenging. Toward this end, we propose novel open-loop and feedback game strategy design approaches for Nash equilibrium and noninferior solutions with a focus on linear quadratic differential games. For the open-loop design, approximate Nash/noninferior game strategies are proposed by integrating distributed state estimation into the open-loop global-information Nash/noninferior strategies such that, without global information, the distributed game strategies can be made arbitrarily close to and asymptotically converge over time to the global-information strategies. For the feedback design, we propose the best achievable performance indices based approach under which the distributed strategies form a Nash equilibrium or noninferior solution with respect to a set of performance indices that are the closest to the original indices. This approach overcomes two issues in the classical optimal output feedback approach: the simultaneous optimization and initial state dependence. The proposed open-loop and feedback design approaches are applied to an unmanned aerial vehicle formation control problem and a multi-pursuer single-evader differential game problem, respectively. Simulation results of several scenarios are presented for illustration
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Optimal Data Scheduling of Clients Serviced using Beamforming Antennas in Mobile Scenarios
Get PDFThe use of beamforming antennas has received significant attention over the last decade. I consider beamforming applied to dynamic operations such as networked UAV hubs which interconnect with users on the ground. The key problem involves understanding how to optimally manage the users' data requirements while considering mobility and a dynamic radio environment serviced by one or more hubs with beamforming antenna capability.
In this work I break the problem down into scheduling, tracking and ultimately execution. I develop a regularized linear programming based scheduling algorithm along with developing a very efficient scheduling with uncertainty receding horizon based relaxation and implement them along with a capacity tracking estimation algorithm. Finally I show the results of successfully implementing this system in hardware using Fidelity Comtech's Phocus Array FCI-3100X.
This implementation shows that the problem overview presented in this work provides a solid basis and defines the key components needed for a reliable electronic beamforming antenna system able to successfully service dispersed users in a mobile environment. It also shows the tools developed, refined, and integrated with respect to tracking, scheduling, and practical modifications
The Effect of Values on System Development Project Outcomes
Get PDFIn order to understand why organizations make certain decisions and target certain outcomes, it is useful to understand their priorities and preferences, commonly referred to as “values.” This research explores the relationship between the technical values held by system development teams and the operational effectiveness of the systems those teams produce. Specifically, it examines the impact of a value set called FIST (Fast, Inexpensive, Simple, Tiny) on DoD and NASA system development projects, and investigates the correlation between the FIST values and operational outcomes. The findings show that the FIST value set enhances project stability, increases the project leader’s control and accountability, optimizes failure, fosters “luck,” and facilitates learning. These benefits of the FIST approach all support the goal of ensuring the organization delivers systems which are “available when needed and effective when used.” FIST is therefore recommended as an effective approach to system development, and several heuristics are provided to facilitate understanding and application of these values
Path planning algorithms for atmospheric science applications of autonomous aircraft systems
No full textAmong current techniques, used to assist the modelling of atmospheric processes, is an approach involving the balloon or aircraft launching of radiosondes, which travel along uncontrolled trajectories dependent on wind speed. Radiosondes are launched daily from numerous worldwide locations and the data collected is integral to numerical weather prediction.This thesis proposes an unmanned air system for atmospheric research, consisting of multiple, balloon-launched, autonomous gliders. The trajectories of the gliders are optimised for the uniform sampling of a volume of airspace and the efficient mapping of a particular physical or chemical measure. To accomplish this we have developed a series of algorithms for path planning, driven by the dual objectives of uncertainty andinformation gain.Algorithms for centralised, discrete path planning, a centralised, continuous planner and finally a decentralised, real-time, asynchronous planner are presented. The continuous heuristics search a look-up table of plausible manoeuvres generated by way of an offline flight dynamics model, ensuring that the optimised trajectories are flyable. Further to this, a greedy heuristic for path growth is introduced alongside a control for search coarseness, establishing a sliding control for the level of allowed global exploration, local exploitation and computational complexity. The algorithm is also integrated with a flight dynamics model, and communications and flight systems hardware, enabling software and hardware-in-the-loop simulations. The algorithm outperforms random search in two and three dimensions. We also assess the applicability of the unmanned air system in ‘real’ environments, accounting for the presence of complicated flow fields and boundaries. A case study based on the island South Georgia is presented and indicates good algorithm performance in strong, variable winds. We also examine the impact of co-operation within this multi-agent system of decentralised, unmanned gliders, investigating the threshold for communication range, which allows for optimal search whilst reducing both the cost of individual communication devices and the computational resources associated with the processing of data received by each aircraft. Reductions in communication radius are found to have a significant, negative impact upon the resulting efficiency of the system. To somewhat recover these losses, we utilise a sorting algorithm, determining information priority between any two aircraft in range. Furthermore, negotiation between aircraft is introduced, allowing aircraft to resolve any possible conflicts between selected paths, which helps to counteractany latency in the search heuristic
Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends
Get PDFGame theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios
The Oxford Democrat: Vol. 77, No. 43 - October 25,1910
Get PDFhttps://digitalmaine.com/oxford_democrat/4724/thumbnail.jp
