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Computationally efficient model predictive control for quasi-Z source inverter based on Lyapunov function

INTERNATIONAL JOURNAL OF modelLING IDENTIFICATION AND control 2020年第4期36卷 342-352页

作者： Minh Khai Nguyen Kim Anh Nguyen Thi Thanh Van Phan Van Quang Binh Ngo Ho Chi Minh City Univ Technol & Educ Dept Elect & Elect Engn Ho Chi Minh City 70000 Vietnam Univ Sci & Technol Univ Danang 54 Nguyen Luong Bang Danang 50000 Vietnam Univ Technol & Educ Univ Danang 48 Cao Thang Danang 50000 Vietnam Hue Univ Univ Educ Fac Phys Thua Thien Hue 49000 Vietnam

This paper proposes a computationally efficient model predictive control strategy for quasi-Z source inverter. Unlike the classical finite control set model predictive control method, besides the ability of computational cost reduction, the proposed method considers the stability of the closed-loop system in the control design. At each sampling period, only feasible switch control inputs that satisfy the stability condition derived from a control Lyapunov function are taken into account in the minimisation of the cost function. Therefore, the computation time of the optimisation problem is decreased compared with the conventional algorithm. A comparison of the classical model predictive control method is investigated by Matlab software in various operating conditions of the system. The achieved results verify the benefit of the proposed approach for dealing with the stability and computational burden over the conventional method while maintaining high control performance.

关键词： quasi-Z source inverter finite control set model predictive control delay compensation computational burden stability condition control Lyapunov function efficient optimisation approach PV system shoot-through (ST) state non-ST state

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FPGA-Based Cost-Effective and Resource Optimized Solution of predictive Direct Current control for Power Converters

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ENERGIES 2021年第22期14卷 7669页

作者： Sankar, Deepa Syamala, Lakshmi Ayyappan, Babu Chembathu Kallarackal, Mathew Cochin Univ Sci & Technol Div Elect Engn Ernakulam 682022 India Mar Athanasius Coll Engn Dept Elect & Commun Engn Kothamangalam 686666 India

Recent advances in power converter applications with highly demanding control goals require the efficient implementation of superior control strategies. However, the real-time application of such control strategies demands high computational power that necessitates efficient digital controllers like field programmable gate array (FPGA). The inherent parallelism offered by FPGAs minimizes the execution time and exhibits an excellent cost-performance trade-off. In addition, rapid advancements in FPGA technology with a broad portfolio of intellectual property (IP) cores, design tools, and robust embedded processors resulted in a design paradigm shift. This article proposes a low-cost solution for the resource-optimized implementation of dynamic, highly accurate, and computationally intensive finite state-predictive direct current control (FS-PDCC). The challenges for implementing complex control algorithms for power converters are discussed in detail, and the control is implemented in Intel's low-cost non-volatile FPGA-MAX (R) 10. An efficient design methodology using finite state machine (FSM) is adopted to achieve time/resource-efficient implementation. The parallel and pipelined architecture of FPGA provides better resource utilization with high execution speed. The experimental results prove the efficiency of FPGA-based cost-effective solutions that offer superior performance with better output quality.

关键词： field programmable gate array intellectual property core finite control set model predictive control finite state machine resource optimization voltage source inverter analog to digital converter

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Robust predictive control of Grid-Side Power Converters for PMSG Wind Turbine Systems with Stability Analysis 21

Robust Predictive Control of Grid-Side Power Converters for ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Wang, Yongdu Zhang, Zhenbin Garcia, Cristian Rodriguez, Jose Kennel, Ralph Shandong Univ Sch Elect Engn Jinan 250061 Peoples R China Shandong Univ Suzhou Inst Suzhou 215123 Peoples R China Univ Talca Dept Elect Engn Talca Chile Univ Andres Bello Fac Ingn Santiago 8370146 Chile Tech Univ Muenchen Inst EAL D-80333 Munich Germany

ISBN: (纸本)9781728157542

Renewable energy plays an increasingly significant role in the power generation process. Wind energy, in particular, has brilliant prospects, especially high-power wind energy. The three-level neutral-point-clamped (3L-NPC) converter for power transformed into the grid has proven to be a promising and effective configuration. For this topology, finite control set model predictive control (FCS-MPC) is an effective control option. However, the performance of FCS-MPC, like most model based control schemes, will deteriorate when system parameter (in particular, the inductance of grid side filters) varies. In this work, we propose a robust FCS-MPC scheme with revised predictions. This proposed robust FCS-MPC outperforms the classic scheme at both normal and parameter mismatched conditions, which has been validated experimentally for such systems with a fully FPGA based real-time hardware. Besides, the proposed method enlarges the range of the stability of the control method. The stability of the proposed scheme is derived theoretically and proven to be better in comparison with classic FCS-MPC.

关键词： Three-level neutral-point-clamped converter finite control set model predictive control robust control stability derivation FPGA

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Long-Horizon Direct model predictive control Based on Neural Networks for Electrical Drives 46

Long-Horizon Direct Model Predictive Control Based on Neural...

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46th Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Hammoud, Issa Hentzelt, Sebastian Oehlschlaegel, Thimo Kennel, Ralph Tech Univ Munich TUM Inst Elect Dr Syst & Power Elect Munich Germany IAV GmbH Powertrain Mechatron Control Engn Excellence Clus Gifhorn Germany

ISBN: (纸本)9781728154145

In this work, the use of a multilayer perceptron feedforward neural network is proposed to capture the solution of the long-horizon finite control set model predictive control (FCS-MPC) problem in electrical drive systems. The motivation behind this research is based on treating the direct model predictive control problem of a power converter as a multi-class classification problem as it consists of a finite set of switching states, which can be seen as a finite number of different classes. By simulation results and hardware in the loop (HIL) test, it is proved that the solution of the long-horizon FCS-MPC can be captured by a real-time computationally implementable neural network that recognizes the converter switching states with an accuracy of 85 - 90%. Hence, it captures the performance enhancement of long horizon FCS-MPC in a computationally efficient manner (15.84 mu s).

关键词： Long horizon direct model predictive control finite control set model predictive control pattern recognition multi-class classification power converters electrical drives

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Flexible Test Bench Arrangement and Particular Implementation of Three Level IGBT Based VSI for Self-sensing model predictive control of Induction Motor 21

Flexible Test Bench Arrangement and Particular Implementatio...

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21st IEEE Workshop on control and modeling for Power Electronics (COMPEL)

作者： Soliman, Ahmed Ibrahim Vedadi, Mohammad Kahia, Billel Abdelrahem, Mohamed Kennel, Ralph Chair Elect Drive Syst & Power Elect Dept Elect & Comp Engn Munich Germany

ISBN: (数字)9781728171609

ISBN: (纸本)9781728171616

In this paper, the main parts of test bench for a self-sensing model predictive control (MPC) technique for an induction motor (IM) operated with IGBT-based three level neutral point clamped voltage source inverters (3L-NPC-VSI) are introduced and discussed. The essential aspects, software and hardware components are discussed, and the crucial required design issues, calculations, layouts, and manufacturing process are illustrated. The MPC algorithm is based on the finite control set (FCS) of the 3L-NPC-VSI, the self-sensing mechanism is based, from one side, on the Extended Kalman Filter (EKF) nonlinear adaptive observer for speed estimation and from other side on the linkage flux estimation for stator flux and motor torque. Transient dynamic behavior of the Motor under different load conditions will be presented and evaluated.

关键词： Induction Motor finite control set model predictive control Direct Torque control 3L-NPC Voltage Source Inverter Extended Kalman Filter Hardware components Bootstrap capacitors signal conditioning Current and voltage measurements Self-sensing

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MPC based controller Design of Battery Integrated Modular Multilevel Converter

MPC based Controller Design of Battery Integrated Modular Mu...

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第40届中国控制会议

作者： Fang Xu Zhongyi Guo Qifang Liu Hong Chen Yali Qu State Key Laboratory of Automotive Simulation and Control Jilin University College of Communication Engineering Jilin University Department of control science and engineering Tongji University Huawei Technologies Co. Ltd.

The control performance of converter directly affects the drive efficiency of electric vehicle（EV）.This paper studies on the model predictive control（MPC） based controller design of battery integrated modular multilevel converter（B-MMC）.Aiming at the goal of three-phase current tracking and battery balancing control of B-MMC,three-layer controllers are *** first controller is the finite control set model predictive control（FCS-MPC）,which realizes the motor drive by tracking the phase *** second controller is the circulation controller for the active balance control of *** is composed of multiple proportional controllers to realize the battery balance between the bridge *** third controller is the battery sorting algorithm to achieve the passive balance control of the battery in the same bridge *** the same time,field programmable gate array（FPGA） is used to accelerate the controller to meet the real-time requirements of ***,the simulation results of the B-MMC control system validates the effectiveness of the control algorithm.

关键词： Electric Vehicle Battery Integrated Modular Multilevel Converter finite control set model predictive control Field Programmable Gate Array

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model predictive controller With Reduced Complexiy or Grid-Tied Multilevel Inverters

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第11期66卷 8851-8855页

作者： Mohapatr, Soumya Ranjan Agarwal, Vivek Indian Inst Technol Mumbai 400076 Maharashtra India

finite control set model predictive control (FCSMPC) has become popular for grid interactive applications due to its simplicity and ease of implementation. Since the implementation of FCSMPC requires all possible switching states of the inverter, the computational burden is an important issue, which needs to be addressed while applying FCSMPC to the control of multilevel inverters. This letter proposes a novel "S" factor scheme for the FCSMPC implementation, which reduces complexity while controlling grid current and balancing the capacitor voltages in neutral point clamped three-level inverters. The proposed scheme is very easy to implement and can be extended to any higher level inverter without any additional effort. In this method, at every sampling instant, redundant switching states are chosen suitably and the predicted reference inverter voltage (PRIV) vector is derived from predicted grid voltage, predicted reference current, and the present value of the actual current. Subsequently, "S" factor scheme is applied to select the switching state, which is close to the PRIV vector. The selected switching state is then applied at the same sampling instant. The proposed scheme is experimentally compared with a recent FCSMPC algorithm to validate the performance.

关键词： Calculation burden finite control set model predictive control grid interactive systems multilevel inverter "S" factor scheme

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Operation and control of Five-level Bi-directional Flying Capacitor DC-DC converter in DC microgrid 4

Operation and Control of Five-level Bi-directional Flying Ca...

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4th IEEE International Future Energy Electronics Conference (IFEEC)

作者： Jayan, Vijesh Ghias, Amer Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781728131535

This paper presents a five-level bi-directional flying capacitor DC-DC converter topology for energy management application in a DC microgrid. Unlike traditional two-level DC-DC converter, the presence of multiple flying capacitors in this topology brings the possibility of having a higher voltage-gain conversion ratio at enhanced efficiency. The existence of five voltage levels give the converter an advantage of having reduced voltage stress on its power switches and a low-sized inductor filter at its input. Additionally, the capability of having bi-directional power flow enables the converter to integrate energy storage devices such as the battery to a high voltage DC microgrid effectively. A finite control set - model predictive control (FCS-MPC) algorithm is formulated using the developed mathematical model in order to yield the multi-objective of bi-directional power flow and three flying capacitor voltage balancing. Furthermore, a DC microgrid comprising photo-voltaic (PV) system, load, and battery are considered to assess the effectiveness of the designed FCS-MPC algorithm under varying load and PV power injections.

关键词： finite control set model predictive control Five Level Bi-directional Flying Capacitor DC-DC converter

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modeling and control of Three-level Bi-directional Flying Capacitor DC-DC converter in DC microgrid 45

Modeling and Control of Three-level Bi-directional Flying Ca...

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45th Annual Conference of the IEEE Industrial Electronics Society (IECON)

作者： Jayan, Vijesh Ghias, Amer Merabet, Adel Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore St Marys Univ Div Engn Halifax NS Canada

ISBN: (纸本)9781728148786

This paper presents a finite control set model predictive control (FCS-MPC) of a three-level bi-directional flying capacitor DC-DC converter for energy management application in a DC microgrid. The presence of three voltage levels give the converter advantage of having reduced voltage stress on the power switches and low ripple in its inductor current. Additionally, the capability of having bi-directional power flow enables the converter to integrate energy storage devices such as the battery to a DC microgrid effectively. An FCS-MPC algorithm is formulated using the developed mathematical model in order to yield the dual objective of bi-directional power flow and flying capacitor voltage balancing. Furthermore, a DC microgrid comprising photo-voltaic (PV) system, load, and battery are considered to assess the effectiveness of the designed FCS-MPC algorithm under varying load and PV power injections.

关键词： finite control set model predictive control Bi-directional Flying Capacitor DC-DC converter

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A Single-Objective FCS-MPC Method for Three-Level APF 11

A Single-Objective FCS-MPC Method for Three-Level APF

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11th Annual IEEE Energy Conversion Congress and Exposition (ECCE)

作者： Peng, Bo Zhang, Guorong Hefei Univ Technol Sch Elect Engn & Automat Hefei Peoples R China

ISBN: (纸本)9781728103952

finite control set model predictive control (FCS-MPC) scheme is applied to active power filter (APF), which has some advantages such as fast dynamic response, needlessness of modulation model. However, some problems exist such as large calculation and difficult selection for weighting factors. In this paper, a single-objective FCS-MPC method is proposed for neutral-point-clamped (NPC) three-level APF. The mixed logic dynamic (MLD) model of APF is built as predictive model. Then based on the traditional FCS-MPC scheme, the proposed method optimized the multiple-objectives by one cost function item without using weighting factors. This method decreases the amount of calculation caused by setting weighting factors and calculating cost function items as well as the number of switch states required to calculate. Finally, simulation and experiment results verify the feasibility and appropriate performance of the proposed method.

关键词： finite control set model predictive control active power filter mixed logic dynamic model cost function

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