2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)最新文献

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An Improved Deadbeat Predictive Current Control for Five-Phase PMSM 一种改进的五相永磁同步电机无差拍预测电流控制
Tianxing Li, Ruiqing Ma
{"title":"An Improved Deadbeat Predictive Current Control for Five-Phase PMSM","authors":"Tianxing Li, Ruiqing Ma","doi":"10.1109/PRECEDE51386.2021.9680897","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680897","url":null,"abstract":"Deadbeat Predictive Current Control (DPCC) has many advantages, but its control effect is highly dependent on the mathematical model and parameter matching degree. As the speed increases, the error between the discrete model obtained by the traditional Euler discrete method and the continuous model will also increase. Besides, the one-step delay control caused by the system delay will also affect the DPCC control effect. In order to improve the control performance of DPCC and the robustness of parameter disturbance, this paper optimizes the traditional DPCC. Firstly, based on the Euler discrete method, the improved prediction model is given to reduce the error caused by discretization, and the influence of parameter disturbance on the improved prediction model is analyzed. Secondly, the system's delay time is obtained according to the current prediction value, reference value, and output voltage vector. And then, the next beat optimal voltage vector is compensated according to the delay time. Finally, a second-order sliding mode observer based on the variable-gain super-twisting algorithm(VA-STA) is proposed, which realizes the observation of parameter errors and compensates the DPCC output results in the form of feed-forward observations.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"234 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122112666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Model Predictive Control of Three-Phase Rectifier for Electric Vehicle Charging 电动汽车充电用三相整流器模型预测控制
Qiaosen Cao, Jianwei Zhang, Haichen Chang, G. Tian
{"title":"Model Predictive Control of Three-Phase Rectifier for Electric Vehicle Charging","authors":"Qiaosen Cao, Jianwei Zhang, Haichen Chang, G. Tian","doi":"10.1109/PRECEDE51386.2021.9680992","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680992","url":null,"abstract":"Model predictive control (MPC) can predict the future behavior of the controlled variable by using the system model and this control method is simple and easy to understand and it has good dynamic performance. This paper investigates an MPC strategy to control a three-phase rectifier for the electric vehicle charging application. The prediction model is established based on input filters of the rectifier and is employed to predict the future behavior of the input current. The output voltage can be effectively regulated and maintained. In addition, the input current and input power factor can be controlled at the same time. A traditional PI controller is also implemented for comparative study. The various comparative simulation results obtained in MATLAB/Simulink verify the feasibility and effectiveness of the proposed predictive control.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129935833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Cascaded predictive Speed Control Optimization Method based on Fuzzy Controller 基于模糊控制器的级联预测速度控制优化方法
T. Guo, Zaixiang Wang, Hao Zhang, Xujie Jiang, Lisi Tian
{"title":"Cascaded predictive Speed Control Optimization Method based on Fuzzy Controller","authors":"T. Guo, Zaixiang Wang, Hao Zhang, Xujie Jiang, Lisi Tian","doi":"10.1109/PRECEDE51386.2021.9680980","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680980","url":null,"abstract":"In a high-performance motor drive system, the motor is required to have fast dynamic response and stable steady-state performance. In the traditional predictive current control, the outer loop still uses the PI controller. Its speed dynamic response is slower than the predictive speed control. Model predictive speed control can improve the dynamic performance of speed, but its steady-state performance is poor and requires high accuracy of motor parameters. At the same time, it is necessary to design a torque observer. This paper proposes an optimization method for predictive speed control based on fuzzy control. The current inner loop of this method uses the continuous control set predictive current control method. The speed outer loop uses both the PI control method and the predictive control method. The fuzzy controller is used to judge the running state of the motor, adjust the output weight of PI control and predictive control, thereby improving the control performance of the motor. The simulation and experimental results prove that the control method proposed in this paper can effectively improve the steady-state performance and robustness of predictive speed control. At the same time, there is no need to design a torque observer.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128400009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Application of Neural Network in Parameters Optimization of Permanent Magnet Synchronous Motor Model Predictive Control 神经网络在永磁同步电机模型预测控制参数优化中的应用
Licheng Liao, Ling Feng, Yuliang Wen, Kaibing Du
{"title":"Application of Neural Network in Parameters Optimization of Permanent Magnet Synchronous Motor Model Predictive Control","authors":"Licheng Liao, Ling Feng, Yuliang Wen, Kaibing Du","doi":"10.1109/PRECEDE51386.2021.9681029","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681029","url":null,"abstract":"This paper proposes a method to realize the parameters optimization of permanent magnet synchronous motor (PMSM) model predictive control (MPC) using neural network (NN). The first step of the method is to use different parameter combinations to perform multiple simulations (or experiments) of the MPC algorithm, and extract the key performance indicators (such as average switching frequency of the inverter, total harmonic distortion, etc.) of the system. Then, train the NN with the acquired data. The trained NN performs as a substitute for the simulation model, and the performance indicators of the system can be estimated quickly and accurately corresponding to arbitrary parameter combinations. Therefore, user can define any fitness function composed of performance indicators, and the optimal parameter combination minimizing the fitness function can be found automatically. Finally, the parameter combinations designed for three different fitness function were verified by simulation, and the predicted performance indicators turned out to be close to the simulation model, with error less than 4%.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130681066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Reduced Complexity Model Predictive Control for Five-Phase Open Winding PMSM Drive 五相开式绕组PMSM驱动器的低复杂度模型预测控制
Mahmoud S. R. Saeed, Wensheng Song, Bin Yu
{"title":"Reduced Complexity Model Predictive Control for Five-Phase Open Winding PMSM Drive","authors":"Mahmoud S. R. Saeed, Wensheng Song, Bin Yu","doi":"10.1109/PRECEDE51386.2021.9680954","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680954","url":null,"abstract":"This paper proposes a simple model predictive current control (MPCC) approach for five-phase open-windings (OW) PMSM drive. In the presented control approach, the control-set is designed by using the virtual voltage vectors (V3s) of the two voltage source inverters (VSIs), which cancel the x-y voltage components. Taking 10 V3s and zero-vector for each VSI, 121 V3s are available as a control-set for the studied system. However, only 21 voltage vectors are selected, which have zero-sequence voltage (ZSV), to remove the zero-sequence current. The best vector is chosen from the 21 candidate vectors according to the information of the reference α-β voltage vector, which is determined by the deadbeat (DB) basis. Hence, the control targets are obtained with the minimum computational load. The capability of the presented MPCC approach is examined using MATLAB simulation.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126408319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Operation Characteristics of Distributed PV based on Measured Data 基于实测数据的分布式光伏发电运行特性研究
Shoubin Diao, Xinpeng Li, Xin Cao, Jian Li, Peixiang Du, Jingru Zhuang
{"title":"Research on Operation Characteristics of Distributed PV based on Measured Data","authors":"Shoubin Diao, Xinpeng Li, Xin Cao, Jian Li, Peixiang Du, Jingru Zhuang","doi":"10.1109/PRECEDE51386.2021.9680899","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680899","url":null,"abstract":"With the increasing penetration of distributed photovoltaic(PV), the fluctuation of high-permeability PV will have a series of impacts on the power grid. The analysis of power quality characteristics at the voltage levels of PV low-voltage grid-connected point (380V) and PV concentrated grid-connected point (10kV) is the basis for the study of PV grid-connected related problems. First, the principle of distributed PV power generation, the principle and structure of grid-connected system, and the influence of grid-connected distributed PV power generation on power grid system are analyzed. Then, based on the measured data of single household distributed PV power generation, the output and operation characteristics of distributed PV power generation are studied. At last, combined with the measured data of PV power generation grid, the multi-index power quality problem of PV power generation grid is analyzed theoretically and experimentally.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132125930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Deadbeat Model Predictive Current Control Algorithm for Modular Multilevel Converters with Enhanced Steady-State Performance 增强稳态性能的模块化多电平变换器无差拍模型预测电流控制算法
Jinyu Wang, Jingjing Huang, Zhijie Liu, Xiong Liu, Zhuo-di Wang
{"title":"A Deadbeat Model Predictive Current Control Algorithm for Modular Multilevel Converters with Enhanced Steady-State Performance","authors":"Jinyu Wang, Jingjing Huang, Zhijie Liu, Xiong Liu, Zhuo-di Wang","doi":"10.1109/PRECEDE51386.2021.9680929","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680929","url":null,"abstract":"Model predictive control (MPC) algorithms are popularly studied for modular multilevel converters (MMCs) because of the multi-objective regulation capability and fast dynamic response. However, they have some inherent drawbacks, for example, calculation complexity, non-fixed switching frequency, complex weighting factor determination as well as weak steady state performance. This article proposes a deadbeat model predictive control algorithm for MMCs. The proposed algorithm can accurately track the reference of output ac and circulating currents in one control period, therefore can provide a fast-dynamic performance. In addition, switching state and cost function calculation and weighting factor determination are removed. Hence, its calculation burden is very low, and not related to the submodules (SMs) number. Since a modulator is adopted, a fixed switching frequency and thus a good steady-state performance are achieved. The impacts of circuit parameter mismatches as well as SM capacitor voltage ripples on the control algorithm are analyzed. Improvement measures are proposed to enhance the steady-state performance and system stability. The effectiveness of the proposed control algorithm is verified by experiments.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129980334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Analysis of the Influence of Nonlinear Flux Models on Predictive Current Control in PMSM Drives 非线性磁链模型对永磁同步电机预测电流控制的影响分析
Zhang Huixuan, Fan Tao, Meng Liu, Bian Yuanjun
{"title":"Analysis of the Influence of Nonlinear Flux Models on Predictive Current Control in PMSM Drives","authors":"Zhang Huixuan, Fan Tao, Meng Liu, Bian Yuanjun","doi":"10.1109/PRECEDE51386.2021.9680971","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680971","url":null,"abstract":"Conventional deadbeat predictive current control is a powerful control strategy for electric drive because of the advantages of fast dynamic response and easy implementation. In this paper, a detailed analysis about the influence of nonlinear flux models on deadbeat control algorithm for PMSM is presented. The concept of tangential inductance and secant inductance are introduced, respectively, and the improved fundamental-wave model is derived. Then the finite element analysis (FEA) results for the tested motor are presented. On this basis, comprehensive simulation results show that the proposed model can effectively improve the control performance of the current loop.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132845928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Experimental Testing of Continious Control Set Model Predictive Control for Three-phase Voltage Source Converters 三相电压源变换器连续控制集模型预测控制的实验研究
M. Mardani, N. Mijatovic, José Raúl Rodríguez Rodríguez, T. Dragičević
{"title":"Experimental Testing of Continious Control Set Model Predictive Control for Three-phase Voltage Source Converters","authors":"M. Mardani, N. Mijatovic, José Raúl Rodríguez Rodríguez, T. Dragičević","doi":"10.1109/PRECEDE51386.2021.9681024","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681024","url":null,"abstract":"Grid-connected voltage source converters (VSCs), which are the key block of the future power electronics-based power systems, are at a high risk of losing stability and robust performance. These challenges in industrial applications require analyzing and designing a simple, robust, and advanced controller to guarantee not only reliable operation but also the performance of the VSCs. This paper proposes a novel constraint and unconstraint continuous control set (CCS) model predictive controller (MPC) for VSCs. In the unconstraint MPC, the optimal control law is analytically calculated. However, for the constraint MPC, the analytical solution is not available. So, the convex optimization methods are used to find the suboptimal solution. Generally, the key novelties of this paper can be enumerated as using CCS-MPC to obtain fixed switching frequency, considering hard constraints on the amplitude of the input and output signals, and analytically obtain the optimal solution for unconstraint MPC. Finally, to evaluate the validity of the proposed approaches, some experimental tests on the laboratory-scale stand-alone VSC are extracted.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131033965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Sensorless Finite Control Set Model Predictive Speed Control of Induction Motor Using Adaptive Full-Order Observer 基于自适应全阶观测器的感应电机无传感器有限控制集预测速度控制
Zhonggang Yin, Qianru Hou, Yanqing Zhang, D. Yuan
{"title":"Sensorless Finite Control Set Model Predictive Speed Control of Induction Motor Using Adaptive Full-Order Observer","authors":"Zhonggang Yin, Qianru Hou, Yanqing Zhang, D. Yuan","doi":"10.1109/PRECEDE51386.2021.9680967","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680967","url":null,"abstract":"In this article, sensorless finite control set model predictive speed control of induction motor using adaptive full-order observer is proposed. Firstly, finite control set model predictive speed control is introduced. It is composed of direct speed control and model predictive control, which gets over the limitations of cascaded structure and obtains high dynamics response. Due to lack of speed loop, stator flux linkage, rotor speed and stator current are taken as the control targets in the cost function. Then, adaptive full-order observer is used to estimate rotor speed and stator flux linkage to improve the reliability and keep the system cost down. Finally, the simulation results indicate that the proposed method has well dynamic performance in the wide speed range.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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