Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp

The goal of this dissertation is to evaluate the effectiveness of model predictive control (MPC) for a magnetically suspended flywheel energy storage uninterruptible power supply (FlyUPS). The reason this research topic was selected was to determine if an advanced control technique such as MPC could...

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Main Author: Aucamp, Christiaan Daniël
Language:en
Published: North-West University 2013
Subjects:
Online Access:http://hdl.handle.net/10394/8601
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-nwu-oai-dspace.nwu.ac.za-10394-86012014-04-16T03:53:14ZModel predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël AucampAucamp, Christiaan DaniëlModel predictive control (MPC)Active magnetic bearings (AMBs)Flywheel energy storage uninterruptible power supply (FlyUPS)Decentralised Proportional-plus-Differential (PD) controlThe goal of this dissertation is to evaluate the effectiveness of model predictive control (MPC) for a magnetically suspended flywheel energy storage uninterruptible power supply (FlyUPS). The reason this research topic was selected was to determine if an advanced control technique such as MPC could perform better than a classical control approach such as decentralised Proportional-plus-Differential (PD) control. Based on a literature study of the FlyUPS system and the MPC strategies available, two MPC strategies were used to design two possible MPC controllers were designed for the FlyUPS, namely a classical MPC algorithm that incorporates optimisation techniques and the MPC algorithm used in the MATLAB® MPC toolbox™. In order to take the restrictions of the system into consideration, the model used to derive the controllers was reduced to an order of ten according to the Hankel singular value decomposition of the model. Simulation results indicated that the first controller based on a classical MPC algorithm and optimisation techniques was not verified as a viable control strategy to be implemented on the physical FlyUPS system due to difficulties obtaining the desired response. The second controller derived using the MATLAB® MPC toolbox™ was verified to be a viable control strategy for the FlyUPS by delivering good performance in simulation. The verified MPC controller was then implemented on the FlyUPS. This implementation was then analysed in order to validate that the controller operates as expected through a comparison of the simulation and implementation results. Further analysis was then done by comparing the performance of MPC with decentralised PD control in order to determine the advantages and limitations of using MPC on the FlyUPS. The advantages indicated by the evaluation include the simplicity of the design of the controller that follows directly from the specifications of the system and the dynamics of the system, and the good performance of the controller within the parameters of the controller design. The limitations identified during this evaluation include the high computational load that requires a relatively long execution time, and the inability of the MPC controller to adapt to unmodelled system dynamics. Based on this evaluation MPC can be seen as a viable control strategy for the FlyUPS, however more research is needed to optimise the MPC approach to yield significant advantages over other control techniques such as decentralised PD control.Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013North-West University2013-06-19T06:12:59Z2013-06-19T06:12:59Z2012Thesishttp://hdl.handle.net/10394/8601en
collection NDLTD
language en
sources NDLTD
topic Model predictive control (MPC)
Active magnetic bearings (AMBs)
Flywheel energy storage uninterruptible power supply (FlyUPS)
Decentralised Proportional-plus-Differential (PD) control
spellingShingle Model predictive control (MPC)
Active magnetic bearings (AMBs)
Flywheel energy storage uninterruptible power supply (FlyUPS)
Decentralised Proportional-plus-Differential (PD) control
Aucamp, Christiaan Daniël
Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
description The goal of this dissertation is to evaluate the effectiveness of model predictive control (MPC) for a magnetically suspended flywheel energy storage uninterruptible power supply (FlyUPS). The reason this research topic was selected was to determine if an advanced control technique such as MPC could perform better than a classical control approach such as decentralised Proportional-plus-Differential (PD) control. Based on a literature study of the FlyUPS system and the MPC strategies available, two MPC strategies were used to design two possible MPC controllers were designed for the FlyUPS, namely a classical MPC algorithm that incorporates optimisation techniques and the MPC algorithm used in the MATLAB® MPC toolbox™. In order to take the restrictions of the system into consideration, the model used to derive the controllers was reduced to an order of ten according to the Hankel singular value decomposition of the model. Simulation results indicated that the first controller based on a classical MPC algorithm and optimisation techniques was not verified as a viable control strategy to be implemented on the physical FlyUPS system due to difficulties obtaining the desired response. The second controller derived using the MATLAB® MPC toolbox™ was verified to be a viable control strategy for the FlyUPS by delivering good performance in simulation. The verified MPC controller was then implemented on the FlyUPS. This implementation was then analysed in order to validate that the controller operates as expected through a comparison of the simulation and implementation results. Further analysis was then done by comparing the performance of MPC with decentralised PD control in order to determine the advantages and limitations of using MPC on the FlyUPS. The advantages indicated by the evaluation include the simplicity of the design of the controller that follows directly from the specifications of the system and the dynamics of the system, and the good performance of the controller within the parameters of the controller design. The limitations identified during this evaluation include the high computational load that requires a relatively long execution time, and the inability of the MPC controller to adapt to unmodelled system dynamics. Based on this evaluation MPC can be seen as a viable control strategy for the FlyUPS, however more research is needed to optimise the MPC approach to yield significant advantages over other control techniques such as decentralised PD control. === Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013
author Aucamp, Christiaan Daniël
author_facet Aucamp, Christiaan Daniël
author_sort Aucamp, Christiaan Daniël
title Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
title_short Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
title_full Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
title_fullStr Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
title_full_unstemmed Model predictive control of a magnetically suspended flywheel energy storage system / Christiaan Daniël Aucamp
title_sort model predictive control of a magnetically suspended flywheel energy storage system / christiaan daniël aucamp
publisher North-West University
publishDate 2013
url http://hdl.handle.net/10394/8601
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