Planner-Based Control of Advanced Life Support Systems 2005-01-2961
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 due to the integration of 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 effective 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.
Citation: Muscettola, N., Kortenkamp, D., Fry, C., and Bell, S., "Planner-Based Control of Advanced Life Support Systems," SAE Technical Paper 2005-01-2961, 2005, https://doi.org/10.4271/2005-01-2961. Download Citation
Author(s):
Nicola Muscettola, David Kortenkamp, Chuck Fry, Scott Bell
Affiliated:
NASA Ames Research Center, Metrica Inc., QSS Group Inc., SKT Inc.
Pages: 11
Event:
International Conference On Environmental Systems
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Life support systems
Control systems
Mathematical models
Simulation and modeling
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