EPSRC Reference: |
GR/N25329/01 |
Title: |
MULTI-SENSOR FUSION ENHANCEMENTS TO MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES |
Principal Investigator: |
Lennox, Professor B |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mechanical Aerospace and Civil Eng |
Organisation: |
University of Manchester, The |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 July 2001 |
Ends: |
31 August 2004 |
Value (£): |
57,067
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EPSRC Research Topic Classifications: |
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EPSRC Industrial Sector Classifications: |
Chemicals |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
A number of review publications portray model predictive control (MPC) as a mature and capable technology. There remain, however, a number of outstanding problems which beset the technology in practical application. The proposed research aims at addressing one such barrier recognised by industry and academia alike as being a principal concern. This issue is that of control under conditions of significant process uncertainty. Specifically we mean the case where significant sections of the plant are judged a-priori as being unreliable - that is, potentially subject to errors and/or failure. This point has been addressed in a somewhat splintered fashion go date, with separation of control and monitoring tasks.The proposed research aims to provide an integrated response to the task of deciding MPC-based actuation moves under system uncertainty. The approach taken involves data-fusion technologies, including density estimation, wavelets and other system representations to define boundaries of reliability on relevant control variables. The programme of work then leads to algorithms for constraint management which respect these boundaries.The approaches developed will be evaluated on benchmark process plant simulations.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.man.ac.uk |