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Optimizing model predictive control of processes for wide ranges of operating conditions

Tran, Vu Nam (2011)
Ph.D. thesis, University of Birmingham.

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Abstract

This thesis develops robustly feasible model predictive controllers (RFMPC) for nonlinear network systems and soft switching mechanism between RFMPCs is proposed to achieve softly switched RFMPC (SSRFMPC).

The safety zones based technique is utilized to design RFMPC by two different mechanisms i.e. iterated safety zones or explicit safety zones. Although the former one is calculated online by the relaxation algorithm and its RFMPC achieve robust feasibility, the recursive robust feasibility is not guaranteed. In contrast to the former, the latter one is calculated off-line and its RFMPC achieves recursive robust feasibility. In addition to this, the robustly feasible invariant sets in the state space are calculated off-line and the initial states need to stay inside those invariant sets in order to achieve feasible control operation.

The computation of RFMPC is very demanding and computing time is reduced by several methods. First, the more efficient optimization solver which is gradient type solver is used to solve the optimization task. The method to provide suitable gradients of objective function and derivatives of constraints to the optimization solver is presented. The robust output prediction is approximated and its horizon is also shortened. The optimization task is formulated in the reduced space of decision variables which is used in the implementation.

The proposed methodology is verified by applying to a simulated drinking water distribution systems example. Comparative simulation results are presented and discussed.

Type of Work:Ph.D. thesis.
Supervisor(s):Brdys, Mietek A.
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:Department of Electronic, Electrical and Computer Engineering
Subjects:TK Electrical engineering. Electronics Nuclear engineering
Institution:University of Birmingham
ID Code:893
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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