Search Results

The purpose of Regenerative Life Support Systems (RLSS) is to support human life by regenerating resources. To date, the design procedure of RLSS has not been generalized as compared with that for automobiles, airplanes, ships or others entities. In this paper, we first analyzed the sub-goals needed to achieve the top-level goal of “support human life by regenerating resources”. This was done by extracting functions to describe each sub-goal and expressing the design process in a hierarchical manner. Next, we proposed the design methodology of determining element attributes to achieve these functions. Furthermore, in this design methodology, the element attributes of systems were determined to ensure the robustness of the systems against unexpected events in material circulation. In this paper, we discuss a generalized-conceptual design methodology for RLSS and apply that concept to Bioregenerative Life Support Systems (BRLSS).

A Regenerative Life Support System (RLSS) is a system that establishes self-sustained material recycling and circulation within a space base on the Moon or Mars. This is a large-scale and complicated system comprising a lot of components such as humans, plants and material circulation system. A RLSS contains many factors with uncertainty, such as dynamics of plants and humans, and failure and performance deterioration of devices. In addition, a RLSS is a large-scale and complicated system extending gradually. An environment with uncertainty or a large-scale and complicated system may not be properly addressed by a centralized system. In particular, such a system cannot always gather accurate information in one center in a frequently shifting environment, thus appropriate processing may be difficult. Therefore, we tried autonomous decentralization of information or decision-making using a Multi-Agent System (MAS).

We developed an Advanced Life Support systems scheduler (ALS scheduler) to back up the habitation experiments of Closed Ecology Experiment Facilities (CEEF), and integrated the Lagrangian decomposition and coordination method for a scheduling algorithm of the scheduler. Later research revealed that when comparing solutions obtained by the Lagrangian decomposition and coordination method and by a skilled operator, respectively, a schedule sought by the skilled operator has different features from those of a schedule sought by the Lagrangian decomposition and coordination method. This paper describes how to generate a schedule such as one created by a skilled operator, while reducing complexity by integrating empirical knowledge to the Lagrangian decomposition and coordination method.

A habitation experiment using the Closed Ecology Experiment Facilities was started in 2005. In the future, the stays will be gradually extended. We have been developing the three layered control software for a Control Computer System of the Closed Ecology Experiment Facilities in order to back up the habitation experiments. In this paper, we will show the development of an operation scheduling system for one of the three layers, such as at the planning and scheduling level, and discuss the development of a scheduling algorithm that does not cause the complexity of the ALS scheduler to be exponentially increased.