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
PY - 2019/3
Y1 - 2019/3
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.
KW - Controller performance
KW - DC-AC power conversion
KW - finite control set model predictive control
KW - statistical model checking
UR - http://www.scopus.com/inward/record.url?scp=85047616412&partnerID=8YFLogxK
U2 - 10.1109/TIE.2018.2838073
DO - 10.1109/TIE.2018.2838073
M3 - Journal article
SN - 0278-0046
VL - 66
SP - 2004
EP - 2014
JO - I E E E Transactions on Industrial Electronics
JF - I E E E Transactions on Industrial Electronics
IS - 3
M1 - 8368064
ER -