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Resumé

A new approach to performance validation of finite control set model predictive control (FCS-MPC) regulated power electronics converters is presented in the paper - statistical model checking (SMC). SMC is an established method used in various sectors of industry to provide solutions to problems that are beyond the abilities of classical formal techniques. The method is simple for implementation and requires only an operational system model that can be simulated and checked against properties. The approach will be presented on a standard 2-level voltage source converter (VSC) regulated by the FCS-MPC algorithm. In UPPAAL SMC toolbox the converter system and controller are modeled as a Network of Stochastic Timed Automata. To assess the quality of the model, an equivalent Simulink model is used as a benchmark model. Using the model created in UPPAAL SMC toolbox the performance of the FCS-MPC algorithm is verified. The control algorithm is also tested on an experimental setup. During the evaluation, no significant degradation of reference tracking was found during transients nor under model parameter uncertainty.
OriginalsprogEngelsk
Artikelnummer8368064
TidsskriftI E E E Transactions on Industrial Electronics
Vol/bind66
Udgave nummer3
Sider (fra-til)2004 - 2014
Antal sider11
ISSN0278-0046
DOI
StatusUdgivet - mar. 2019

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Power converters
Model checking
Model predictive control
Power electronics
Degradation
Controllers
Statistical Models
Electric potential
Industry

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title = "Analytical Design and Performance Validation of Finite Set MPC Regulated Power Converters",
abstract = "A new approach to performance validation of finite control set model predictive control (FCS-MPC) regulated power electronics converters is presented in the paper - statistical model checking (SMC). SMC is an established method used in various sectors of industry to provide solutions to problems that are beyond the abilities of classical formal techniques. The method is simple for implementation and requires only an operational system model that can be simulated and checked against properties. The approach will be presented on a standard 2-level voltage source converter (VSC) regulated by the FCS-MPC algorithm. In UPPAAL SMC toolbox the converter system and controller are modeled as a Network of Stochastic Timed Automata. To assess the quality of the model, an equivalent Simulink model is used as a benchmark model. Using the model created in UPPAAL SMC toolbox the performance of the FCS-MPC algorithm is verified. The control algorithm is also tested on an experimental setup. During the evaluation, no significant degradation of reference tracking was found during transients nor under model parameter uncertainty.",
keywords = "Controller performance, DC-AC power conversion, finite control set model predictive control, statistical model checking",
author = "Mateja Novak and Nyman, {Ulrik Mathias} and Tomislav Dragicevic and Frede Blaabjerg",
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Analytical Design and Performance Validation of Finite Set MPC Regulated Power Converters. / Novak, Mateja; Nyman, Ulrik Mathias; Dragicevic, Tomislav; Blaabjerg, Frede.

I: I E E E Transactions on Industrial Electronics, Bind 66, Nr. 3, 8368064, 03.2019, s. 2004 - 2014.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Analytical Design and Performance Validation of Finite Set MPC Regulated Power Converters

AU - Novak, Mateja

AU - Nyman, Ulrik Mathias

AU - Dragicevic, Tomislav

AU - Blaabjerg, Frede

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N2 - A new approach to performance validation of finite control set model predictive control (FCS-MPC) regulated power electronics converters is presented in the paper - statistical model checking (SMC). SMC is an established method used in various sectors of industry to provide solutions to problems that are beyond the abilities of classical formal techniques. The method is simple for implementation and requires only an operational system model that can be simulated and checked against properties. The approach will be presented on a standard 2-level voltage source converter (VSC) regulated by the FCS-MPC algorithm. In UPPAAL SMC toolbox the converter system and controller are modeled as a Network of Stochastic Timed Automata. To assess the quality of the model, an equivalent Simulink model is used as a benchmark model. Using the model created in UPPAAL SMC toolbox the performance of the FCS-MPC algorithm is verified. The control algorithm is also tested on an experimental setup. During the evaluation, no significant degradation of reference tracking was found during transients nor under model parameter uncertainty.

AB - A new approach to performance validation of finite control set model predictive control (FCS-MPC) regulated power electronics converters is presented in the paper - statistical model checking (SMC). SMC is an established method used in various sectors of industry to provide solutions to problems that are beyond the abilities of classical formal techniques. The method is simple for implementation and requires only an operational system model that can be simulated and checked against properties. The approach will be presented on a standard 2-level voltage source converter (VSC) regulated by the FCS-MPC algorithm. In UPPAAL SMC toolbox the converter system and controller are modeled as a Network of Stochastic Timed Automata. To assess the quality of the model, an equivalent Simulink model is used as a benchmark model. Using the model created in UPPAAL SMC toolbox the performance of the FCS-MPC algorithm is verified. The control algorithm is also tested on an experimental setup. During the evaluation, no significant degradation of reference tracking was found during transients nor under model parameter uncertainty.

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KW - statistical model checking

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