Imperial College London
Alternate

Dr Imad M. Jaimoukha

Faculty of Engineering, Department of Electrical and Electronic Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 6279i.jaimouka Website

 
 
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Location

 

617Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Tahir:2013:10.1016/j.jprocont.2012.08.003,
author = {Tahir, F and Jaimoukha, IM and Tahir, F and Jaimoukha, IM},
doi = {10.1016/j.jprocont.2012.08.003},
journal = {Journal of Process Control},
pages = {189--200},
title = {Robust Feedback Model Predictive Control of Constrained Uncertain Systems},
url = {http://dx.doi.org/10.1016/j.jprocont.2012.08.003},
volume = {23},
year = {2013}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We propose a novel procedure for the solution to the problem of robust model predictive control (RMPC) of linear discrete time systems involving bounded disturbances and model-uncertainties along with hard constraints on the input and state. The RMPC (outer) controller - responsible for steering the uncertain system state to a designed invariant (terminal) set - has a mixed structure consisting of a state-feedback component as well as a control-perturbation. Both components are explicitly considered as decision variables in the online optimization and the nonlinearities commonly associated with such a state-feedback parameterization are avoided by adopting a sequential approach in the formulation. The RMPC controller minimizes an upper bound on an H2/H_infinity-based cost function. Moreover, the proposed algorithm does not require any offline calculation of (feasible) feedback gains for the computation of the RMPC controller. The optimal Robust Positively invariant set and the inner controller - responsible for keeping the state within the invariant set - are both computed in one step as solutions to an LMI optimization problem. We also provide conditions which guarantee the Lyapunov stability of the closed-loop system. Numerical examples, taken from the literature, demonstrate the advantages of the proposed scheme.
AU  - Tahir,F
AU  - Jaimoukha,IM
AU  - Tahir,F
AU  - Jaimoukha,IM
DO  - 10.1016/j.jprocont.2012.08.003
EP  - 200
PY  - 2013///
SP  - 189
TI  - Robust Feedback Model Predictive Control of Constrained Uncertain Systems
T2  - Journal of Process Control
UR  - http://dx.doi.org/10.1016/j.jprocont.2012.08.003
VL  - 23
ER  -
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