A Novel Framework for Advanced Life Support Systems Control

The Advanced Life Support (ALS) systems are one of the key enablers of long-duration human space exploration. These systems are complex, often involving interactions between biological and physicochemical systems. Each of these systems is made out of multiple, coupled loops (for example fluid flow, energy management, thermal control, gas transfer, bio- regeneration and chemical production loops). In the case of long duration missions, given the limited resupply capability, it is desirable that consumables (oxygen, water) are recycled as much as possible with minimum losses, leading to the fact that these loops should be closed. Furthermore, since these life support systems perform different functions, they operate at different rates; in order to have the whole system performing properly, buffers need to be introduced between these sub-systems to accommodate different flow rates. Models of ALS behavior must capture system dynamics at appropriate time scales and at multiple physical domains, giving rise to complex simulations. This paper describes a framework for analyzing ALS in terms of three main design variables: loop closure rate, buffer size and system control complexity. Efforts to date have focused on point designs for ALS – selecting an architecture based on a set of system combinations and analyzing its performance. We believe that more progress can be achieved in the ALS field if a methodology was devised for rapid system assessment based on key system parameters, then studying the tradespace formed with different architecture combinations to identify a few promising candidates, which will then be subjected to in-depth, higher fidelity simulations. After describing this framework and the variables and parameters it is based on, this paper proceeds to examine a selection of case studies. Lastly, we investigate the effect of low-level control on systems and show that simple control can result in an improvement of the endurance of 46%.