Real-Time Implementation of Long-Horizon Direct Model Predictive Control on an Embedded System

This paper deals with the real-time implementation of a long-horizon finite control set model predictive control (FCS-MPC) algorithm on an embedded system. The targeted application is a medium-voltage drive system which means that operation at a very low switching frequency is needed so that the switching power losses are kept relatively low. However, a small sampling interval is required to achieve a fine granularity of switching, and thus ensure superior system performance. This renders the real-time implementation of the controller challenging. To facilitate this, a high level synthesis (HLS) tool, which synthesizes C++ code into VHDL, is employed to enable a higher level of abstraction and faster prototype development of the real-time solver of the long-horizon FCS-MPC problem, namely the sphere decoder. Experimental results based on a small-scale prototype, consisting of a three-level neutral point clamped (NPC) inverter and an induction machine, confirm that the algorithm can be executed in real time within the targeted control period of 25 $\mu$s.publishedVersionPeer reviewe

2-(2-Methyl-5-nitro-1H-imidazol-1-yl)ethyl N-methyl­carbamate

In the title compound, C8H12N4O4, the essentially planar methyl­carbamoyloxymethyl group [maximum deviation 0.038 (3) Å] and the imidazole ring make a dihedral angle of 48.47 (3)°. The crystal packing is stabilized by inter­molecular N—H⋯N and C—H⋯O hydrogen bonds, which link the mol­ecules into infinite ribbons running along the a axis, and by weak π–π stacking inter­actions [centroid–centroid distance = 3.894 (2) Å]

A Direct Model Predictive Control Strategy of Back-to-Back Modular Multilevel Converters Using Arm Energy Estimation

This paper presents a model predictive control (MPC) algorithm for modular multilevel converters (MMCs). To meet the control objectives of phase current reference tracking and circulating current minimization, the proposed control scheme calculates the optimal number of submodules (SMs) to be inserted in each arm. In doing so, favorable steady-state and dynamic performance is achieved. More-over, by estimating-instead of measuring-the arm energies in the predictive stage of the control loop, the proposed control scheme results in self-stabilizing open-loop arm energy balancing, while avoiding potential stability issues. Furthermore, to reduce the computational complexity of the MPC algorithm, the optimization problem is simplified by controlling each phase separately and assuming that the SM capacitors are balanced within an arm. To ensure that this assumption is always satisfied, a subsequent capacitor voltage balancing algorithm is designed to select the individual SMs that are switched on and off. The performance of the proposed control strategy is validated with simulations for a high voltage dc system (HVDC) that consists of two MMCs with 20 SMs per arm in a back-to-back configuration.acceptedVersionPeer reviewe

Implementation of a Long-Horizon Model Predictive Control Algorithm on an Embedded System

This paper deals with the implementation of a long-horizon finite control set model predictive control (FCS-MPC) algorithm on an embedded system. The targeted application is a medium voltage drive system implying a very low switching frequency. The implementation is facilitated by the use of a high level synthesis (HLS) tool, which synthesizes C++ code into VHDL, enabling a higher level of abstraction and faster prototype development. Experimental results based on a small-scale prototype, consisting of a three-level neutral point clamped (NPC) inverter and an induction machine, confirm that the algorithm can be executed in real time within the targeted control period of 25μs. This allows for high switching granularity, and thus favorable steady-state and transient performance.acceptedVersionPeer reviewe

Three-Level Optimized Pulse Patterns With Reduced Common-Mode Voltage

This paper proposes the computation of three-level optimized pulse patterns (OPPs) with reduced common-mode voltage (CMV) over the whole range of modulation indices. Limiting the CMV, however, gives rise to increased current harmonics. To mitigate this, the OPP optimization problem is reformulated to allow for symmetry relaxations and multipolar switch positions. In doing so, the current harmonics not only remain low, but they are occasionally even lower than those of traditional OPPs. The presented numerical results, based on a medium-voltage (MV) drive consisting of a three-level converter and an induction machine, demonstrate the benefits of the proposed approach.acceptedVersionPeer reviewe

Long-Horizon Robust Direct Model Predictive Control for Medium-Voltage Drives with Active Neutral-Point Potential Balancing

The paper presents a direct model predictive control algorithm for medium-voltage (MV) induction machines driven by three-level neutral-point-clamped (NPC) inverters that incorporates the neutral point potential balancing. For such nonlinear systems implementation of long horizons may be regarded as even a formidable task due to the high computational complexity. Nevertheless, this can be achieved with a modest calculation cost by decreasing the size of the underlying control optimization problem. Moreover, when assisted by a light estimation algorithm, the developed control scheme achieves a high level of robustness to variations in the motor parameters. The presented results demonstrate the effectiveness of the proposed method during steady-state and transient operating conditions.Peer reviewe

A Computationally Efficient Robust Direct Model Predictive Control for Medium Voltage Induction Motor Drives

Long-horizon direct model predictive control (MPC) has pronounced computational complexity and is susceptible to parameter mismatches. To address these issues, this paper proposes a solution that enhances the robustness of long-horizon direct MPC, while keeping its computational complexity at bay. The former is achieved by means of a suitable prediction model of the drive system that enables the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed approach is demonstrated with a medium-voltage (MV) drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM).acceptedVersionPeer reviewe

Long-Horizon Direct Model Predictive Control with Reduced Computational Complexity

The paper proposes a strategy that reduces the computational burden of enumeration-based direct model predictive control (MPC) with long prediction intervals. This is achieved by combining a move blocking scheme with an educated restriction of the set of candidate solutions. To demonstrate the effectiveness of the proposed algorithm, a two-level converter connected to the grid via an LCL filter serves as a case study.Peer reviewe

Long-Horizon Robust Direct Model Predictive Control for Medium-Voltage Induction Motor Drives With Reduced Computational Complexity

This paper proposes a long-horizon direct model predictive control (MPC) with reference tracking for medium-voltage (MV) drives that achieves favorable steady-state and transient behavior. However, as MPC is a model-based method, it is susceptible to parameter mismatches and variations of the machine. Moreover, even though a long prediction horizon significantly improves the steady-state behavior of the drive, it significantly increases the computational complexity of the direct MPC problem, rendering its real-time implementation a challenging—if not impossible—task. Motivated by these shortcomings of long-horizon direct MPC, this paper also aims to address them by enhancing the robustness of the developed control strategy, while keeping its computational complexity modest. To achieve the former, a prediction model suitable for MV drive systems is adopted that facilitates the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed modeling, control, and estimation approaches is validated with hardware-in-the-loop (HIL) tests for an MV drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM).acceptedVersionPeer reviewe