| EPSRC Reference: |
EP/C513584/1 |
| Title: |
Uncertainty and Risk Optimisation Algorithms For Food Processing |
| Principal Investigator: |
Rustem, Professor B |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Computing |
| Organisation: |
Imperial College London |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 June 2005 |
Ends: |
31 August 2008 |
Value (£): |
239,507
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Design of Process systems |
| Parallel Computing |
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| EPSRC Industrial Sector Classifications: |
| Food and Drink |
Information Technologies |
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Summary on Grant Application Form |
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This is a joint project between University of Birmingham and Imperial College London.Food processes are limited by uncertainty in design. The need to ensure safety means that they are significantly overdesigned. This project addresses this problem by combining novel experimental and modelling techniques.The purpose of the proposed project is to develop tools for optimisation of non-linear dynamic systems under uncertainty, decision support and scenario analysis problems in food processing and process design. Many food processes have to be specified using uncertain data and physical properties. Any improvement in the design solutions would deliver both higher food quality and better process safety. The problem is how to use the limited data available to give the best result.The system is characterised by equations comprising state (dependent) variables and decision (control) variables as well as uncertain variables. Simple bounds and inequalities define the operational region for controls and states. The optimisation uses an elimination of the state variables from the problem using a computable mapping (i.e., model solution program or differential algebraic solver) between the states and control variables. Worst-case design provides a systematic and quantitative way of ensuring the safety of any process, given a model of its (dynamic) behaviour. The proposed project will explore a generic approach to non-linear expected value optimisation, as well as higher order moments optimisation to cover nonlinearities in uncertain variables.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.imperial.ac.uk |