2021-04-122018-02-011955251319552505WOS;000424264600025SCOPUS;2-s2.0-84979608107http://hdl.handle.net/10784/29048Numerical optimization solve problems efficiently where such efficiency is focused on the speed with which the optimal x* is achieved, is open line of research and strong work in the scientific community in order to achieve control systems in dynamic processes with response times of the order of milliseconds. A clear example of this, is the implementation of optimal controller’s combustion engines. For subsequent approach to the design and implementation of nonlinear model predictive control controllers, it has made a comparison of yields algorithms quadratic programming by active set with linearization restrictions, and sequential quadratic programming with single shooting technique to solve quadratic optimization problem formulation referred to a dynamic internal combustion engine of spark ignition, in embedded systems with real-time processing. © 2016, Springer-Verlag France.https://v2.sherpa.ac.uk/id/publication/issn/1955-2513info:eu-repo/semantics/articleCombustionCombustion equipmentComputer control systemsEmbedded systemsEnginesIgnitionIgnition systemsInternal combustion enginesModel predictive controlOptimizationPredictive control systemsProblem solvingQuadratic programmingReal time controlReal time systemsAutomotiveDesign and implementationsHard-ware-in-the-loopNonlinear model predictive controlOptimal controlsQuadratic optimization problemsSequential quadratic programmingSimulationControllers2021-04-12Chica, J.A.V.Torres, A.G.D.Acosta Maya, Diego Andres10.1007/s12008-016-0343-2