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. Index Terms-Controller performance, DC-AC power conversion, finite control set model predictive control, statistical model checking.

Model Predictive Control of Power Electronic Systems: Methods, Results, and Challenges

“…Moreover, closed-loop stability of one-step direct MPC was achieved in [178] by introducing constraints that ensure the asymptotic convergence of the controlled variables. Furthermore, an interesting approach for the verification of the behavior of direct MPC for different power electronic was proposed in [179]. By employing tools from statistics, this work aims to take the relevant research one step further than [174], [175].…”

Microsecond nonlinear model predictive control for DC‐DC converters

“…using Equation (18). Figure 2 contains the simulated transient response of the state variables in the boost converter with NMPC applied for the different values of the switching prediction horizon N ∈ {1, 2, 10}.…”

“…Since these converters are new and prominent, and moreover very important for future energy development, the control methods are also being rapidly developed. MPC methods found their application for the control of two‐level converters using finite control set MPC. Similarly, there are efficient algorithms for finite control set MPC for the AC‐DC converters as in Richter et al and for matrix converters .…”

Finite Set MPC Algorithm for Achieving Thermal Redistribution in a Neutral-Point-Clamped Converter

“…The weighting factors in the cost functions (λ dc = 1, λ t = 0.05) were determined by running multiple simulations. A concept for selecting weighting factors presented in [27] can be used to find the optimum solution. For this system the THD, DC-link balance and junction temperature difference can be defined as the performance metrics.…”