Number representation in predictive control

Show simple item record Kerrigan, Eric C. Jerez, Juan L. Longo, Stefano Constantinides, George A. 2019-04-11T18:01:52Z 2019-04-11T18:01:52Z 2012-09-30
dc.identifier.citation Eric C. Kerrigan, Juan L. Jerez, Stefano Longo and George A. Constantinides. Number representation in predictive control. IFAC Proceedings Volumes, Volume 45, Issue 17, 2012, pp. 60-67 en_UK
dc.identifier.issn 1474-6670
dc.description.abstract In predictive control a nonlinear optimization problem has to be solved at each sample instant. Solving this optimization problem in a computationally efficient and numerically reliable fashion on an embedded system is a challenging task. This paper presents results to reduce the computational requirements for solving fundamental problems that arise when implementing predictive controllers in finite precision arithmetic. By employing novel formulations and tailor-made optimization algorithms, this paper shows that computational resources can be reduced using very low precision arithmetic. We also present new mathematical results that enable computational savings to be made in the most numerically critical part of an optimization solver, namely the linear algebra kernel, using fixed-point arithmetic. Our theoretical results are supported by numerical results from implementations on a Field Programmable Gate Array (FPGA). en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject Predictive control en_UK
dc.subject Optimization problems en_UK
dc.subject Number systems en_UK
dc.subject Numerical methods en_UK
dc.subject Embedded systems en_UK
dc.title Number representation in predictive control en_UK
dc.type Article en_UK

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