Nonlinear Model Predictive Control for Stochastic Differential Equation Systems

Niclas Laursen Brok; Henrik Madsen; John Bagterp Jørgensen

doi:10.1016/j.ifacol.2018.11.071

Nonlinear Model Predictive Control for Stochastic Differential Equation Systems

Niclas Laursen Brok^*, Henrik Madsen, John Bagterp Jørgensen

^*Corresponding author for this work

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Abstract

Using the Van der Pol oscillator model as an example, we provide a tutorial introduction to nonlinear model predictive control (NMPC) for systems governed by stochastic differential equations (SDEs) that are observed at discrete times. Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time. Furthermore, this representation directly facilities construction of the state estimator in the NMPC. We provide numerical details related to systematic model identification, state estimation, and optimization of dynamical systems that are relevant to the NMPC.

Original language	English
Book series	I F A C Workshop Series
Volume	51
Issue number	20
Pages (from-to)	430-435
ISSN	1474-6670
DOIs	https://doi.org/10.1016/j.ifacol.2018.11.071
Publication status	Published - 2018

Keywords

Continuous-Discrete Extended Kalman Filter
Maximum Likelihood Estimation
Nonlinear Model Predictive Control
Stochastic Differential Equations
Van der Pol Oscillator

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title = "Nonlinear Model Predictive Control for Stochastic Differential Equation Systems",

abstract = "Using the Van der Pol oscillator model as an example, we provide a tutorial introduction to nonlinear model predictive control (NMPC) for systems governed by stochastic differential equations (SDEs) that are observed at discrete times. Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time. Furthermore, this representation directly facilities construction of the state estimator in the NMPC. We provide numerical details related to systematic model identification, state estimation, and optimization of dynamical systems that are relevant to the NMPC.",

keywords = "Continuous-Discrete Extended Kalman Filter, Maximum Likelihood Estimation, Nonlinear Model Predictive Control, Stochastic Differential Equations, Van der Pol Oscillator",

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T1 - Nonlinear Model Predictive Control for Stochastic Differential Equation Systems

AU - Brok, Niclas Laursen

AU - Madsen, Henrik

AU - Jørgensen, John Bagterp

PY - 2018

Y1 - 2018

N2 - Using the Van der Pol oscillator model as an example, we provide a tutorial introduction to nonlinear model predictive control (NMPC) for systems governed by stochastic differential equations (SDEs) that are observed at discrete times. Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time. Furthermore, this representation directly facilities construction of the state estimator in the NMPC. We provide numerical details related to systematic model identification, state estimation, and optimization of dynamical systems that are relevant to the NMPC.

AB - Using the Van der Pol oscillator model as an example, we provide a tutorial introduction to nonlinear model predictive control (NMPC) for systems governed by stochastic differential equations (SDEs) that are observed at discrete times. Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time. Furthermore, this representation directly facilities construction of the state estimator in the NMPC. We provide numerical details related to systematic model identification, state estimation, and optimization of dynamical systems that are relevant to the NMPC.

KW - Continuous-Discrete Extended Kalman Filter

KW - Maximum Likelihood Estimation

KW - Nonlinear Model Predictive Control

KW - Stochastic Differential Equations

KW - Van der Pol Oscillator

U2 - 10.1016/j.ifacol.2018.11.071

DO - 10.1016/j.ifacol.2018.11.071

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SP - 430

EP - 435

JO - I F A C Workshop Series

JF - I F A C Workshop Series

IS - 20

ER -

Nonlinear Model Predictive Control for Stochastic Differential Equation Systems

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Keywords

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