Development of theoretical approaches to the control of a water-treatment system

作者：Chiam Tze Chao; Yih Yuehwern^*; Mitchell Cary

来源：Advances in Space Research, 2010, 46(11): 1418-1426.

DOI：10.1016/j.asr.2010.08.022

• Baseline Values and Assumptions Document
• Control policies
• Markov Decision Process
• State-space exploration
• Probability convergence

The Advanced Life Support/NASA Specialized Center of Research and Training (ALS/NSCORT) focuses on research and development of technologies to support human habitation during space missions. This research was done as part of an effort to maintain crew-members' water supply in a closed life-support system. The water subsystem was the primary focus of this study because water is one of the most expensive and important resources for human survival.
This paper focuses on the application of previously-developed methodologies for controlling a water-treatment system. The water-treatment and usage model was set up based on the Baseline Value and Assumptions Document (BVAD) published by NASA. The conditions, or "states", of the system are captured hourly in the model. Control policies are defined in terms of treatment efficiencies. One control policy is to be used for the system at the beginning of each hour. A simulation is developed to study the impact of different control policies to this model. The Markov Decision Process (MDP) is used to aid the decision of choosing a policy to be used.
In order for the MDP to pick the best policy, a state-space exploration technique, the Controlled Random Walk, is used for state-space exploration. This technique, together with re-initialization of initial system conditions, allow the system to visit a larger portion of the state space compared to some other techniques.
In order to describe the state transitions, transition-probability matrices need to be computed. A probability-convergence technique is developed to minimize bias while computing these matrices. This technique is based on the Kullback-Leibler divergence measure, but modified for this application.
A test case is constructed to assess the performance of best policies. Three scenarios with different levels of fluctuation, or disturbances, of water-consumption and treatment efficiencies are introduced in the test case. Results show that the best policies outperformed cases where fixed policies, as well as random policies, are used in all three scenarios.

• 出版日期2010-12-1