Imperial College London
Portrait Picture

ProfessorEricKerrigan

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Control and Optimization
 
 
 
//

Contact

 

+44 (0)20 7594 6343e.kerrigan Website

 
 
//

Assistant

 

Mrs Raluca Reynolds +44 (0)20 7594 6281

 
//

Location

 

1114Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{McInerney:2020,
author = {McInerney, I and Kerrigan, E and Constantinides, G},
pages = {1--4},
publisher = {IFAC Secretariat},
title = {Closed-form preconditioner design for linear predictive control},
url = {https://ism.engineer/content/papers/2020_IFAC-WC_PreconditionerDesign.pdf},
year = {2020}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Model Predictive Control (MPC) with linear models and constraints is extensivelybeing utilized in many applications, many of which have low power requirements and limitedcomputational  resources.  In  these  resource-constrained  environments,  many  designers  chooseto utilize simple iterative first-order optimization solvers, such as the Fast Gradient Method.Unfortunately, the convergence rate of these solvers is affected by the conditioning of the problemdata, with ill-conditioned problems requiring a large number of iterations to solve. In order toreduce  the  number  of  solver  iterations  required,  we  present  a  simple  closed-form  method  forcomputing an optimal preconditioning matrix for the Hessian of the condensed primal problem.To  accomplish  this,  we  also  derive  spectral  bounds  for  the  Hessian  in  terms  of  the  transferfunction of the predicted system. This preconditioner is based on the Toeplitz structure of theHessian and has equivalent performance to a state-of-the-art optimal preconditioner, withouthaving to solve a semidefinite program during the design phase.
AU  - McInerney,I
AU  - Kerrigan,E
AU  - Constantinides,G
EP  - 4
PB  - IFAC Secretariat
PY  - 2020///
SN  - 2405-8963
SP  - 1
TI  - Closed-form preconditioner design for linear predictive control
UR  - https://ism.engineer/content/papers/2020_IFAC-WC_PreconditionerDesign.pdf
UR  - http://hdl.handle.net/10044/1/79359
ER  -
Download