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Details of Grant 

EPSRC Reference: GR/M07328/01
Title: ROBUST CONTROL, FAULT DETECTION AND STATISTICAL PROCESS CONTROL
Principal Investigator: McFarlane, Professor D
Other Investigators:
Vinnicombe, Dr G Vinnicombe, Dr G Glover, Professor K
Researcher Co-Investigators:
Project Partners:
Department: Engineering
Organisation: University of Cambridge
Scheme: Standard Research (Pre-FEC)
Starts: 01 August 1998 Ends: 31 January 1999 Value (£): 7,000
EPSRC Research Topic Classifications:
Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
The work will involve applying methods of robust filtering and prediction to problems of fault detection and diagnosis and realted problems of model validation and stistical process control (SPC). Robust filtering and predicion involved constructing a state estimate for a given system based on an uncertain system model and these ideas fit in naturally woth problems of fault detection and diagnosis. Simliar ideas can also be applied to problems of model validation and dynamic SPC. In practice the dynamic model required for dynamic SPC will be subject to uncertaincies. Hence, we will apply techniques developed in the theory of robust filtering to the problem of robust SPC for the case in which the underlying dynamic model is uncertain.Also the project will look at problems of robust control with IQC uncertainty and in particular connections to the v(nu) gap approah. These ideas will also be applied to problems of fault detection and model validation. The v(nu) gap approach has already proved a useful tool for looking at the realtive importance of perturbations in a system model. However it does not easilt deal with nonlinear time varying dynamic perturbations. Such perturbations are frequently dealt with using an IQC uncertainty framework and hence the IQC uncertainty description appears to provide a natural extension to the existing v(nu) gap ideas.
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Organisation Website: http://www.cam.ac.uk