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  • 1.
    Garg, Kanika
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Wind Based Navigation for Zero-Pressure Stratospheric Balloons Using Reinforcement learning2019In: Acta Astronomica, ISSN 0001-5237Article in journal (Refereed)
    Abstract [en]

    The horizontal motion of the balloon is governed by the winds at the float altitude. In order to navigate, and change the direction of balloon flight, knowledge of the wind environment around the balloon is needed. The real time navigation and control of zero-pressure balloons is a challenging task as there are no sensors that can be used onboard the balloon to provide real knowledge of the wind environment. Further, their is no active actuation possible and the resources available for passive actuation are limited. These constraints makes the balloon flight difficult and inflexible. In this paper, a solution to this problem of balloon navigation, and its path planning is presented by using data from ECMWF in combination with reinforcement learning. Data from ECMWF gives an overview of almost real-time environment and a reinforcement learning algorithm help in optimizing the passive actuation resources.

  • 2.
    Matelli, José Alexandre
    et al.
    São Paulo State University (UNESP), School of Engineering, Department of Energy, Av. Ariberto Pereira da Cunha, Guaratinguetá, SP, Brazil.
    Goebel, Kai
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. NASA Ames Research Center, Intelligent Systems Division, Discovery and Systems Health, Moffett Field, CA.
    Resilience evaluation of the environmental control and life support system of a spacecraft for deep space travel2018In: Acta Astronomica, ISSN 0001-5237, Vol. 152, p. 360-369Article in journal (Refereed)
    Abstract [en]

    In deep space manned travels, the crew life will be totally dependent on the environment control and life support system of the spacecraft. A life-support system for manned missions is a set of technologies to regenerate the basic life-support elements, such as oxygen and water, which makes resilience a paramount feature of this system. The resilience of a complex engineered system is the ability of the system to withstand failures, continue operating and recover from those failures with minimum disruption. Resilient design is a new design framework on which the main goal is to quantify system resilience upfront in order to guide the design team during the conceptual design stage. In this article, we present a tool that combines a rule-based approach with a Monte Carlo-based approach to evaluate the resilience of a proposed environment control and life support system designed for deep space travel. Based on the results found, we explore a few design alternatives in order to increase system resilience.

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