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Details of Grant 

EPSRC Reference: GR/R15481/01
Title: Robust Model Prediction Control of Constrained Dynamic Systems
Principal Investigator: Vinter, Professor RB
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Electrical and Electronic Engineering
Organisation: Imperial College London
Scheme: Standard Research (Pre-FEC)
Starts: 01 June 2001 Ends: 31 March 2003 Value (£): 219,596
EPSRC Research Topic Classifications:
Control Engineering
EPSRC Industrial Sector Classifications:
Energy Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
Nearly every application imposes hard constraints on states and controls. Determination of a feedback law when hard constraints are present is often numerically impossible. Model predictive control is one of very few methods available for the handling of such constraints and is, for this reason, the preferred method of control in some sectors of the process industry with over 2000 applications. But a fundamental defect in conventional model predictive control, namely that the optimal control problem solved on-line is open-loop, has not been adequately addressed with the consequence that this controller does not adequately account for uncertainty .The first aim of this project is to remedy this defect by development of feedback model predictive control characterised by an optimal control problem, solved on-line, whose solution provides a local feedback strategy; the uncertainties addressed in this research include state estimation error, external disturbances and modelling error. The second objective is the development of a numerically viable method, implemented in MATLAB, for computing robust state and output feedback control laws for linear constrained systems. The third objective is the extension of this approach to nonlinear systems. The final objective is to apply this approach to a set of relevant examples.
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Organisation Website: http://www.imperial.ac.uk