A Reverse Model Predictive Control Strategy for a Modular Multilevel Converter

Abstract

In recent years, modular multilevel converters (MMCs) have developed rapidly, and are widely used in medium and high voltage applications. Model predictive control (MPC) has attracted wide attention recently, and its advantages include straightforward implementation, fast dynamic response, simple system design, and easy handling of multiple objectives. The main technical challenge of the conventional MPC for MMC is the reduction of computational complexity of the cost function without the reduction of control performance of the system. Some modified MPC scan decrease the computational complexity by evaluating the number of on-state sub-modules (SMs) rather than the number of switching states. However, the computational complexity is still too high for an MMC with a huge number of SMs. A reverse MPC (R-MPC) strategy for MMC was proposed in this paper to further reduce the computational burden by calculating the number of inserted SMs directly, based on the reverse prediction of arm voltages. Thus, the computational burden was independent of the number of SMs in the arm. The control performance of the proposed R-MPC strategy was validated by Matlab/Simulink software and a down-scaled experimental prototype.

RBF Neural Network-Based Sliding Mode Control for Modular Multilevel Converter with Uncertainty Mathematical Model

“…Then, various nonlinear control techniques, such as sliding mode control [7], Lagrange multiplier-based optimal control [8], model-based input-output linearization [9], and developed feedback linearization [10], have also been proposed and researched. Another control approach is model predictive control [12][13][14]. It was originally proposed by Richalet and Cutleris and now is widely used in power electronics.…”

Improved model predictive control for modular multilevel converter with reduced voltage sensors based on Kalman filter

“…So that, for structures with a large number of SMs, the number of switching states compared to the previous methods is reduced, but the computational burden depends on the number of SMs. In References 10‐12, the control of MMC with N + 1 output voltage levels is proposed. This design has fewer total harmonic distortion (THD) on the output voltage compared to the previous design with 2N + 1 output voltage levels, but this method cannot ensure the controllability of the circulating current 7 .…”

High frequency signal injection method for sensorless permanent magnet synchronous motor drives

“…In this paper, only FCS-MPC (or MPC for short) is considered since it has proven to perform better with less complexity and has been applied to various types of applications such as power electronics converters and motor drives. Thus, this paper present the design of the two popular types of MPC known as model predictive torque control (MPTC) and model predictive current control (MPCC) [32][33][34][35][36][37]. Detail performance investigation is carried out in term of load and unload conditions comparing the four main type of high-performance drive control structures which are the MPTC, MPCC, FOC and DTC.…”