Modeling, Design and Simulation of a Reconfigurable Aquatic Habitat for Life Support Control Research

42nd International Conference on Environmental Systems

Howard

2012

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A limitation in closed-loop life support system research is the no-availability of smallscale experimental capacities that may help to better understand the challenges in system closure, integration, and control. Ground-based aquatic habitats are an option for smallscale research relevant to bioregenerative life support systems (BLSS), given that they can operate as self-contained systems enclosing a habitat composed of various species in a single volume of water. This paper elaborates on the modeling, design, and simulation of a reconfigurable aquatic habitat for experiments in BLSS and automation. It focuses in the process of respiration: higher plants of the species Bacopa Monnieri produce O2 for snails of the genus Pomacea. The snails consume the O2 and generate CO2, which is used by the plants in combination with radiant energy to generate O2 through the process of photosynthesis. The paper expands the description of biological processes by introducing models of ecophysiological phenomena of the organisms involved. The model of the plants include a description of the rate of CO2 assimilation as a function of irradiance. The snails instead are modeled through their rate of consumption, treated as a combination of a constant and a random variable to account for changes in metabolic rates and aestivation. The latter consists in brief periods of torpor of the metabolism of the snails in which oxygen consumption is considerably reduced. Simulations and validation runs with hardware show how these phenomena may act as disturbances for the control mechanisms that aim to maintain safe concentration levels of dissolved oxygen in the habitat.

Section: Discussionmentioning

confidence: 99%

Section: A Simulationsmentioning

confidence: 99%

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Ecophysiological Models in Simulations of an Aquatic Habitat for Closed-Loop Life Support Research

42nd International Conference on Environmental Systems

Howard

2012

Self Cite

“…The model of the aquatic habitat [24] focuses on the process of respiration. Dissolved oxygen is consumed by the aquatic organisms at the same time they exhale CO 2 as a by-product.…”

Section: The Reconfigurable Aquatic Habitat a Preliminary Descriptionmentioning

confidence: 99%

A granular approach to the automation of bioregenerative life support systems that enhances situation awareness

2012 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support

Howard

2012

Bioregenerative life support systems introduce novel challenges for the development of model-based approaches to their control given the varying characteristic of the biological processes that constitute them. Switching control paradigms provide an alternative to manage such uncertainty by allowing flexibility into the control path, enabling different control modes depending on the situation of the system. This paper presents a perceptionbased approach that combines sensor information to define those conditions and act upon them. Combined sensor information creates sensing spaces in which the operational conditions of the system are found. The decomposition of the sensing spaces into perceptual elements or granules allows for situation assessment, system integration strategies, and the implementation of fail-safe and fail-operational mechanisms -all these critical in a wider range of complex socio-technical systems. This paper proposes the use of intelligent agents based on fuzzy associative memories (FAM's) to decompose sensing spaces into granular structures composed of n-dimensional non-interactive fuzzy sets. Granular structures resulting from such decomposition allow for the incremental development and automation of the system by associating a control task to each operational condition. Furthermore, the real-time information obtained from the membership value of the granules may provide a resource for situational awareness and for the design of new ecological interfaces to enhance humansystem interaction and real-time decision making. The approach presented in this paper is applied to the dynamic model of a reconfigurable aquatic habitat that serves as a small-scale bioregenerative test bed for life support control research. Results show how information generated by the FAM enhances the situation observability of the system.

“…A model of an aquatic habitat 19 was used to perform simulations of anomalies that exhibit transitions between various operation conditions. The purpose was to operate under all possible situations so that data could be collected.…”

Section: Implementation In a Small-scale Aquatic Habitatmentioning

confidence: 99%

A Granular Multi-Sensor Data Fusion Method for Situation Observability in Life Support Systems

42nd International Conference on Environmental Systems

Howard²

2012

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Slow-changing characteristics of controlled environmental systems and the increasing availability of data from sensors and measurements offer opportunities for the development of computational methods to enhance situation observability, decrease human workload, and support real-time decision making. Multi-sensor data fusion, which combines observations and measurements from different sources to provide a complete description of a system and its environment, can be used in user-centered interfaces in support situation awareness and observability. Situation observability enables humans to perceive and comprehend the state of the system at a given instant, and helps human operators to decide what actions to take at any given time that may affect the projection of such state into the near future. This paper presents a multi-sensor data fusion method that collects discrete human-inputs and measurements to generate a granular perception function that supports situation observability. These human-inputs are situation-rich, meaning they combine measurements defining the operational condition of the system with a subjective assessment of its situation. As a result, the perception function produces situation-rich signals that may be employed in user-interfaces or in adaptive automation. The perception function is a fuzzy associative memory (FAM) composed of a number of granules equal to the number of situations that may be detected by human-experts; its development is based on their interaction with the system. The human-input data sets are transformed into a granular structure by an adaptive method based on particle swarms. The paper proposed describes the multi-sensor data fusion method and its application to a ground-based aquatic habitat working as a small-scale environmental system. Nomenclature x Measured Variable X Universe of Discourse for x X α Subset α in X µ(x) Membership Function in xÃ Granular Structure P * Parameter Solution