Nonlinear control of electronic converters

Abstract

This thesis considers the design of the sampling-driven nonlinear model predictive controller (SD-NMPC) for power electronic converters. Most MPC schemes that are used nowadays lack in the application for systems with high sampling frequencies because of their high computational time, especially when the system is nonlinear. This is, for example, the case for most of the power electronic systems. Recently, a new approach of MPC control is proposed which is based on sampling control inputs from the input space. In contrast with other MPC approaches, this approach is focused on suboptimal control instead of the optimal control in other MPC approaches which usually results in a less optimal control sequence, but, furthermore, it still benefits from all the advantages of the MPC control method. This thesis describes several efficient and fast methods to determine the offline part of the SD-NMPC controller, which are the local controller with corresponding DOA and the initial control sequence steering the system into this DOA, using only linear optimization tools. Among all these methods, we determined the best option for the buck-boost converter with resistive load and the VSI controlling a PMSM. Besides the offline part, we also improved the online part of the SD-NMPC control method which resulted in a fast and optimal controller for these systems. This method has shown all the benefits of the implementation of an MPC controller. Based on the results, we could conclude that the SD-NMPC control method is a fast and efficient way to apply an MPC method to power electronic converters.