Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/8151
Title: Runge-Kutta model-based adaptive predictive control mechanism for non-linear processes
Authors: Iplikçi, Serdar
Keywords: Extended Kalman filter
non-linear model predictive control
optimal control
parameter estimation
Adaptive predictive control
Continuous-time
Discrete models
Generalized predictive control
Nonlinear model predictive control
Nonlinear process
Online parameter adaptation
Optimal controls
Extended Kalman filters
Model predictive control
Nonlinear systems
Parameter estimation
Runge Kutta methods
Predictive control systems
Abstract: This paper proposes a novel non-linear model predictive control mechanism for non-linear systems. The idea behind the mechanism is that the so-called Runge-Kutta model of a continuous-time non-linear system can be regarded as an approximate discrete model and employed in a generalized predictive control loop for prediction and derivative calculation purposes. Additionally, the Runge-Kutta model of the system is used for state estimation in the extended Kalman filter framework and online parameter adaptation. The proposed method has been tested on two different non-linear systems. Simulation results have revealed the effectiveness of the proposed method for different cases. © 2012 The Author(s).
URI: https://hdl.handle.net/11499/8151
https://doi.org/10.1177/0142331212438910
ISSN: 0142-3312
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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