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Title: The Application of Multi-Agent Systems to the Design of an Intelligent Geometry Compressor
Author: Morgan, Gwyn
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2002
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In this research, a multi-agent approach was applied to the design of a large axial flow compressor in order to optimise performance and to greatly enlarge the useful operating range of the machine. In this design a number of distributed software/hardware agents co-operate to control the internal geometry of the machine and thereby optimise the compressor characteristics in response to changes in flow conditions. The resulting machine is termed an ‘Intelligent Geometry Compressor’ (IGC). The design of a multi-agent system for the IGC was carried out in three main phases, each supported by computer simulation. In the first phase a steady-state model of the IGC was developed in which global control of the variable geometry is achieved by a single agent. This was used to help identify specific requirements for performance and the underlying parametric relationships. The subsequent phases incorporated additional agents into the machine design to meet these requirements. Initially, agents were deployed to optimise the settings of individual rows of stator vanes. In the final phase, the MAS was extended to incorporate agents into the machine design for the control of individual stator vanes. Simulation results were obtained which demonstrate the effectiveness of the intelligent geometry compressor in achieving delivery pressure regulation over a wide range of steady-state operating conditions whilst optimising overall machine efficiency and avoiding the occurrence of stall. Some of the implications for the physical design of an IGC arising from the MAS concept were briefly considered. The experience of the research supported by the specific results and observations from many simulation trials, led to the conclusion that multi-agent systems can provide an effective and novel alternative approach to the design of an intelligent geometry compressor. By implication, this conclusion may be extended to other intelligent machine applications where similar opportunity to apply a distributed control solution exists.
Supervisor: Rzevski, G. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Multi-Agent Systems ; Variable geometry compressor Hydraulic machinery Pneumatic machinery Artificial intelligence Automatic control Control theory