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Closure experiments will be conducted using the Closed Plant Experiment Facility (CPEF) and the Closed Animal and Habitation Experiment Facility (CAHEF) of the Closed Ecology Experiment Facilities (CEEF). The CEEF behavioral Prediction System (CPS) has been developed to check the CEEF operation for the closure experiments in advance. For the development of CPS, a simulation program for CPEF had been developed and reported. A simulation program for CAHEF was developed, and combined with the simulation program for CPEF. This integrated simulation program was validated by data obtained from a habitation experiment conducted in CEEF.

This paper discusses the integration of intelligence into the supervision and control system of an Advanced Life Support System (ALSS). An ALSS is a complex, large-scale system that should be maintained solely by a small crew. Since an ALSS is operated far from Earth, the propagation delay of radio waves makes remote support from Earth difficult to implement immediately. Accordingly, an autonomous supervision and control system is essential. A supervision and control system comprises an automatic controller for ALSS equipment and crew who supervise the equipment conditions and operate it. The application of intelligent control to such an automatic controller reduces the load on the crew, allowing them to concentrate on their major missions. The concept of intelligent control proposed here is based on the SRK model that expresses human behavior with three cognitive behaviors. This paper utilizes simulation to verify the effectiveness of the proposed methods for intelligent control.

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.

In this paper, we describe the design of intelligent control software required for operating the Closed Ecology Experiment Facilities (CEEF) that we call Mini-Earth. We will develop intelligent control software by reconfiguring functions of a Control Computer System (CCS) for controlling the CEEF into three layers that consist of planning & scheduling, task, and control levels. In the last half of this paper, we will focus on the planning & scheduling level, and describe the operation scheduling problem of a CEEF gas circulation system using a Planning and Scheduling Language (PSL) to develop an Operation Schedule Interactive Generation system (OSIG).

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.