Feedback linearization-based current control strategy for modular multilevel converters

Modular multilevel converters (MMCs) are multi-input multi-output (MIMO) nonlinear systems. The control systems for MMCs are required to simultaneously achieve multiple control objectives, e.g., output current regulation, submodule capacitor voltage control, and circulating ripple currents suppressi...

Full description

Bibliographic Details
Main Authors: Yang, Shunfeng, Wang, Peng, Tang, Yi
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141589
Description
Summary:Modular multilevel converters (MMCs) are multi-input multi-output (MIMO) nonlinear systems. The control systems for MMCs are required to simultaneously achieve multiple control objectives, e.g., output current regulation, submodule capacitor voltage control, and circulating ripple currents suppression. Existing cascaded control strategies for MMCs achieve those control objectives with relatively complex controllers, and the controller parameter design is normally difficult for such nonlinear systems with highly coupled states. In view of this, a feedback linearization-based current control strategy is proposed for an MMC system in this paper. The nonlinear state function model of the MMC is presented and transformed to a linearized and decoupled form with the help of the input-output feedback linearization technique. Based on the linearized system, simple linear controllers are employed to regulate the output and inner differential currents of the MMC, which significantly reduces the difficulty in controller design. The stability of the proposed control strategy is analyzed. The experimental verification results show that, compared to the conventional cascaded control strategies for MMCs, the proposed feedback linearization control strategy is able to achieve improved steady-state and dynamic performances. The robustness of the proposed control strategy against parametric uncertainties is experimentally investigated.