Multi-agent diagnosis and control of an air revitalization system for life support in space

Malin, Jane T.; Kowing, Jeffrey; Schreckenghost, Debra; Bonasso, Pete; Nieten, J.; Graham, John L.; Fleming, Land; MacMahon, Matt; Thronesbery, Carroll

doi:10.1109/aero.2000.877906

Cited by 15 publications

(8 citation statements)

References 7 publications

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“…The development of agent technology provides us not only with new computing methods and paradigms, but also with a good solution for the implementing of CIMS. For example, using the methods and ideas of agent research, we can construct a DAS (data acquisition system) based on agent technology and benefit from intelligent data acquisition technology [8][9][10][11][12][13][14][15][16][17][18].…”

Section: Agent and Distributed Intelligencementioning

confidence: 99%

Intelligent Data Acquisition Technology Based on Agents

Shuzi

2003

The International Journal of Advanced Manufacturing Technology

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Nowadays, information is the most important factor for any manufacturing enterprise. Information helps a manufacturer to make decisions about management, production, operation, maintenance, and repair. Information technology is a key for enterprises who are realising integrated manufacturing all over the world. Data acquisition is the backbone of information technology. Data acquisition technology is the product of the fusion and interaction of many technologies. It is necessary to develop new data acquisition technology and methods by using the recently produced research results. It is also important for realising manufacturing automation, promoting product quality, and enhancing the competitive ability of an enterprise. In this paper, we first analyse three common kinds of data acquisition mode and their features used in manufacturing systems. Then, based on the background of manufacturing automation, agents and distributed artificial intelligent technology, which form a new data acquisition model framework suitable for an advanced manufacturing system, is proposed, and some details about this new model are discussed. Two examples of this model used in manufacturing systems are then given to show the availability and correctness of this model framework. We conclude with current research results in this area and give an outline of future work.

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Section: Agent and Distributed Intelligencementioning

confidence: 99%

Intelligent Data Acquisition Technology Based on Agents

Shuzi

2003

The International Journal of Advanced Manufacturing Technology

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“…New methods and techniques that accommodate the new trends of digital, intelligence, decentralization and globalization in the manufacturing process, are urgently needed. Intelligent condition monitoring, distributed condition monitoring and Internet/intranet condition monitoring developed in recent years, which are more suitable for modern manufacturing technology, are the typical paradigms [3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Distributed flexible reconfigurable condition monitoring and diagnosis technology

Shuzi

You-min

2006

Front. Mech. Eng. China

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As manufacturing becomes increasingly decentralized, flexible and reconfigurable, more research needs to be done on monitoring and diagnosis technology that accommodate these new trends. The distributed condition monitoring and diagnosis technology based on the "flexible and reconfigurable" concept is studied here. A condition monitoring diagnosis model based on the distributed flexible and reconfigurable idea is proposed in this paper. The component makeup and functions of this model are discussed in detail. The model can fulfill in most instances the manufacturing system requirements for changing the configuration of the monitoring diagnosis system according to different manufacturing system configurations. This model also realizes the flexibility and reconfigurability of the monitoring diagnosis system in some degree. The model has already spawned a successful prototype for monitoring a chemical plant in accomplishing monitoring and control of the production process and equipment. Finally, some future research work is pointed out.

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“…In particular, we consider the control problem of a Variable Configuration CO 2 Removal (VCCR) system, which exhibits a hybrid dynamical character due the various configurations/modes in which one could operate the system. The VCCR is part of an overall Air Recovery System (Finn, 1999;Malin, et al, 2000), which in turn is part of an intended human life-support system for space exploration. The paper is organized as follows: Section II presents the configuration and hybrid dynamic model of the VCCR system, Sections III and IV present the nonlinear model predictive control synthesis, and Section V presents simulation results.…”

Section: Introductionmentioning

confidence: 99%