Intelligent Control of Product Gas Transfer for Air Revitalization

Schreckenghost, Debra; Edeen, Marybeth A.; Bonasso, R. Peter; Erickson, Jon D.

doi:10.4271/981705

Cited by 12 publications

(5 citation statements)

References 4 publications

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“…In 1997, the ALS group experimented with four people in a thirty-foot chamber for ninety-one days [6]. A physicalchemical air revitalization system (ARS) recycled the air for three of the four people, while a wheat crop in the ten-foot chamber did the same for the fourth.…”

Section: T Als Effortsmentioning

confidence: 99%

Requirements for an Autonomous Control Architecture for Advanced Life Support Systems

Biswas

Bonasso

Abdelwahed

et al. 2005

SAE Technical Paper Series

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This paper describes a series of life support control experiments at NASA Johnson Space Center and at Vanderbilt University. These experiments involved two distinct, layered control architectures; one used a modelbased approach and the other a procedural approach to control complex, distributed systems. Both sets of experiments produced good results, but it also brought out the strengths and weaknesses of the two underlying technologies. Our goal in this paper is to come up with the requirements for an integrated architecture for autonomous controller design that combines the best of the two approaches. This paper discusses a potential approach to this integration and the advantages it offers.

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Section: T Als Effortsmentioning

confidence: 99%

Requirements for an Autonomous Control Architecture for Advanced Life Support Systems

Biswas

Bonasso

Abdelwahed

et al. 2005

SAE Technical Paper Series

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“…A JSC advanced development group has developed an autonomous control system to operate the product gas transfer phase of Bioplex [15]. This system, based upon the 3T autonomy architecture [16], maintains the appropriate atmosphere in each chamber by extracting and storing product gases and coordinating activities such as firing the incinerator or opening the plant chamber for human access.…”

Section: Closed-loop Ecological Life Support Systems (Celss)mentioning

confidence: 99%

Model-based system-level health management for reusable launch vehicles

Clancy

2000

Space 2000 Conference and Exposition

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The next generation of reusable launch vehicles are expected to radically reduce the cost of accessing space thus enabling a broad range of endeavors including the commercialization of space and further manned exploration of the inner solar system. A reduction in operational costs requires more sophisticated techniques for monitoring and controlling the vehicle while in flight and techniques to streamline the ground processing of the vehicle. For both tasks, it is often necessary to synthesize information obtained from multiple subsystems to detect and isolate both hard failures and degraded component performance.Traditionally, the synthesis of information from multiple components or subsystems is performed by skilled ground control and maintenance teams, hi the future, much of this task will need to be performed by more sophisticated software systems that are able to reasoning about subsystem interactions. Performing this task using a traditional software programming paradigm is challenging due to the myriad of interactions that occur between subsystems especially when one of more components are performing in some off-nominal fashion. Model-based programming addresses this limitation by encoding a high-level qualitative model of the device being monitored. Using this model, the system is able to reason generatively about the expected behavior of the system under the current operating conditions, detect off-nominal behavior and search for alternative hypotheses that are consistent with the available observations. In this paper, we will talk about the Livingstone model-based health management system. Livingstone was initially developed and demonstrated as part of the Remote Agent Experiment on Deep Space One. Future flight experiments are planned for both the X-34 and the X-37 reusable launch vehicles.

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“…Routine control of an ALS system is well within the reach of current techniques. For example, the autonomous control system described in [4] operated around the clock for 73 straight days during a 90 day crewed test with minimal human intervention. The autonomous control system for a recent test of an advanced water recovery system operated with minimal human intervention for over eighteen months [5].…”

Section: Introductionmentioning

confidence: 99%

Planner-Based Control of Advanced Life Support Systems

Muscettola¹,

Kortenkamp²,

Fry³

et al. 2005

SAE Technical Paper Series

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The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems.Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics that emerge when integrating a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster, simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction.In particular, methods from model-based planning and scheduling can provide optimal resource management over long time periods. We describe a reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control.We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

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Intelligent Control of Product Gas Transfer for Air Revitalization

Cited by 12 publications

References 4 publications

Requirements for an Autonomous Control Architecture for Advanced Life Support Systems

Requirements for an Autonomous Control Architecture for Advanced Life Support Systems

Model-based system-level health management for reusable launch vehicles

Planner-Based Control of Advanced Life Support Systems

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