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

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Reinforcement Learning Based Weighting Factor Design of Model Predictive Control for Power Electronic Converters 基于强化学习的电力电子变流器模型预测控制加权因子设计
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680964
Yihao Wan, T. Dragičević, N. Mijatovic, Chang Li, José Raúl Rodríguez Rodríguez
{"title":"Reinforcement Learning Based Weighting Factor Design of Model Predictive Control for Power Electronic Converters","authors":"Yihao Wan, T. Dragičević, N. Mijatovic, Chang Li, José Raúl Rodríguez Rodríguez","doi":"10.1109/PRECEDE51386.2021.9680964","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680964","url":null,"abstract":"Weighting factor design is one of the challenges for finite-set model predictive control (FS-MPC) controlled power electronic converters, which plays an important role in the balance of control objectives in the cost function to achieve desired performance. This paper investigates the application of reinforcement learning algorithm for the weighting factor design for FS-MPC regulated voltage source converter in uninterrupted power supply (UPS) system. The deep deterministic policy gradient (DDPG) agent is employed to learn the optimal weighting factor design policy. The reinforcement learning (RL) agent is trained in the system and the weighting factor is optimized based on reward calculation with the interactions between the agent and environment. The key performance metric, total harmonic distortion (THD), is incorporated in the reward function. Effectiveness of the proposed reinforcement learning based weighting factor design method is validated by simulations.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"326 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":"115765156","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
Finite-Set Model Predictive Current-Control in Field Weakening Region for Linear Induction Machines 线性感应电机弱磁场区域有限集模型预测电流控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680948
M. Elmorshedy, Wei Xu
{"title":"Finite-Set Model Predictive Current-Control in Field Weakening Region for Linear Induction Machines","authors":"M. Elmorshedy, Wei Xu","doi":"10.1109/PRECEDE51386.2021.9680948","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680948","url":null,"abstract":"The main purpose for the execution of this strategy is to control the linear induction machines (LIMs) over the rated linear speed. This is developed by one field weakening by finite-set model predictive current control (FW-FSMPCC). The reference values of Id and Iq are continuously adapted as a function to control the speed. This enhances the drive capability where the machine can work under both rated speed and over rated speed. The maximum current and voltage are taken into consideration to keep the machine working with safe operation. Only the primary currents are used in the optimized cost function and therefore no weighting factor is needed like the thrust control. The primary current errors would occur in αβ-coordinates, which is estimated by considering the absolute value of subtraction of primary reference current from the predicted primary current. The end-effect phenomenon is also taken under consideration for the design process of the suggested control method and for dynamic model of the LIM. All theoretical analysis has been validated by comprehensive simulation results based on parameters of one arc induction machine with estimated power 3 kW and large radius.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"62 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":"124264159","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
Comparison of Finite Control Set Model Predictive Control Methods for Five-Level NNPC Inverter 五电平NNPC逆变器有限控制集模型预测控制方法的比较
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9681030
Hua Liao, T. Jin, D. L. Mon‐Nzongo, Jinquan Tang, Ziqiang Liu
{"title":"Comparison of Finite Control Set Model Predictive Control Methods for Five-Level NNPC Inverter","authors":"Hua Liao, T. Jin, D. L. Mon‐Nzongo, Jinquan Tang, Ziqiang Liu","doi":"10.1109/PRECEDE51386.2021.9681030","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681030","url":null,"abstract":"Based on the topology of five level nested neutral point clamped (NNPC) grid connected inverter, this paper compares two type of finite control set model predictive control (FCS-MPC) methods to reduce the amount of calculation time compare with the traditional FCS-MPC. The first method is based on space vector modulation approach which uses 60- degree voltage state vector for the prediction to reduce the calculation time of each control period in FCS-MPC algorithm. While the second method is to simplify the calculation time by using the FCS-MPC based on adjacent state vector method. Through comparative analysis, it can be seen that the 60 degrees sector FCS-MPC have similar performances regarding the current THD; the upper and lower DC voltage deviation of DC- link capacitors. The main difference is on the computation time which results to 35 control periods compare to 125 for the traditional FCS-MPC. The adjacent state vector method results to 7-29 control period.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"60 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":"116700112","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
Model Predictive Control of a DFIG-Based Wind Turbine Using Three-Level NPC Converter 基于dfig的三电平NPC变换器风力机模型预测控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9681039
Xuanguang Zhang, Z. Xie, Xing Zhang, Shuying Yang
{"title":"Model Predictive Control of a DFIG-Based Wind Turbine Using Three-Level NPC Converter","authors":"Xuanguang Zhang, Z. Xie, Xing Zhang, Shuying Yang","doi":"10.1109/PRECEDE51386.2021.9681039","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9681039","url":null,"abstract":"The three-level NPC converters applied in wind power is increasing, but the traditional control strategy of doubly-fed induction generator (DFIG) cannot balance the midpoint voltage well, and the modulation algorithm is more complicated. This paper establishes the mathematical models of DFIG and NPC converters, and uses the characteristics of model predictive control multi-objective optimization to control the three-level converter on the machine side to improve the performance of the system. At the same time, the preselected vector is optimized, which reduces the average switching frequency and computational complexity of the control algorithm. Finally, simulations verify the effectiveness of the proposed control strategy.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"27 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":"117156662","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
Model Predictive Direct Torque Control for PMSM Drives in M–T Frame M-T框架PMSM驱动的模型预测直接转矩控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680934
Changliang Dang, M. Dou, Yuanlin Wang
{"title":"Model Predictive Direct Torque Control for PMSM Drives in M–T Frame","authors":"Changliang Dang, M. Dou, Yuanlin Wang","doi":"10.1109/PRECEDE51386.2021.9680934","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680934","url":null,"abstract":"Model predictive control (MPC) is attracting interests due to many of its advantages, such as fast dynamic response and no need for modulators. However, the changes of system parameters affect the accuracy of the prediction results. Hence, this paper proposes a novel Model Predictive Direct Torque Control (MP-DTC) method for permanent magnet synchronous motor (PMSM) drives in M-T frame, which is synchronized with the stator flux linkage vector. Thus, the entire control system for PMSM drives operates under the M–T coordinate system, which reveals an attractiveness of parameter insensitivity and simple calculation. The simulation and experiment result demonstrate the validity and effectiveness of the proposed control strategy.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"81 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":"125179886","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: 4
The Influence of Weighing Factor and Prediction Horizon on the Dynamic Performance of the Model Predictive Current Control 称重因子和预测范围对模型预测电流控制动态性能的影响
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680917
Sixun Du, Liwei Chen, Yuanlin Wang, M. Dou
{"title":"The Influence of Weighing Factor and Prediction Horizon on the Dynamic Performance of the Model Predictive Current Control","authors":"Sixun Du, Liwei Chen, Yuanlin Wang, M. Dou","doi":"10.1109/PRECEDE51386.2021.9680917","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680917","url":null,"abstract":"Model predictive current control (MPCC) has been widely studied due to its excellent performances. Generally, the weighting factor in the cost function is omitted, based on the consideration that the dimensions of id and iq are the same. Besides, many papers states that the number of predicted steps does not affect the dynamic performance. In this paper, the relationship between the dynamic performances of id and iq is studied, it is proved that the weighing factor affects the current dynamic performance obviously. A cost function that compares the last predicted currents with the reference currents is proposed, the dynamic performance can be improved with long horizon prediction. The influence of weighting factor and prediction steps on dynamic performance of MPCC are validated by experiments.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"619 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":"123271369","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
Robust Predictive Current Control of Dual Three-phase PMSM Using Prediction Error Correction 基于预测误差校正的双三相永磁同步电机鲁棒预测电流控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680937
Rong Fu
{"title":"Robust Predictive Current Control of Dual Three-phase PMSM Using Prediction Error Correction","authors":"Rong Fu","doi":"10.1109/PRECEDE51386.2021.9680937","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680937","url":null,"abstract":"Model predictive current control of dual three-phase permanent magnet synchronous motor (PMSM) has become a research hotspot because of its intuitive concept, less controller parameters and easy to handle fault-tolerant control and nonlinear constraints. However, mismatched motor parameters lead to stator current prediction error. To solve this problem, a robust predictive current control with prediction error correction (PEC-RPCC) is proposed in this paper, where a correction term is added to stator current prediction equation. The correction term consists of the difference between the predicted value and the sampled value of the stator current in the previous step. Simulation results verify the effectiveness of the method.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"119 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":"123477764","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
Starting Control of Three-stage Synchronous Motor based on Improved Current-coordinated Vector Control 基于改进电流协调矢量控制的三级同步电动机起动控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680915
Hong Zhu, Lie Xu, Yongdong Li, Kui Wang, Yuanli Kang, Yannian Hui
{"title":"Starting Control of Three-stage Synchronous Motor based on Improved Current-coordinated Vector Control","authors":"Hong Zhu, Lie Xu, Yongdong Li, Kui Wang, Yuanli Kang, Yannian Hui","doi":"10.1109/PRECEDE51386.2021.9680915","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680915","url":null,"abstract":"Compared with traditional aircraft technology, more electric/all electric aircraft has larger capacity, simplified structure, higher power density and equipment utilization. At present, the most widely used three-stage synchronous motor starter/generator system in more electric aircraft has also become an important research content. An improved current-coordinated vector control method based on model predictive control is proposed for starting control of three-stage synchronous motor. This method does not require complex flux observer, makes full use of the excitation current of three-stage synchronous motor. The simulation results show that the method improves the dynamic response performance and parameter robustness of the system, which is beneficial to practical engineering application. (Abstract)","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"34 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":"115525739","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
[PRECEDE 2021 Front cover] [pre 2021年封面]
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/precede51386.2021.9681012
{"title":"[PRECEDE 2021 Front cover]","authors":"","doi":"10.1109/precede51386.2021.9681012","DOIUrl":"https://doi.org/10.1109/precede51386.2021.9681012","url":null,"abstract":"","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"30 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":"114185730","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 Model-Free Current Prediction Control with Runge-Kutta Algorithm for Grid-Connected Inverter 基于龙格-库塔算法的并网逆变器无模型电流预测控制
2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) Pub Date : 2021-11-20 DOI: 10.1109/PRECEDE51386.2021.9680905
Guanglu Yang, Han Xiao, Yifeng Sun, Zhifeng Dou, Wenhui Wang, Zhiguo Wang
{"title":"A Model-Free Current Prediction Control with Runge-Kutta Algorithm for Grid-Connected Inverter","authors":"Guanglu Yang, Han Xiao, Yifeng Sun, Zhifeng Dou, Wenhui Wang, Zhiguo Wang","doi":"10.1109/PRECEDE51386.2021.9680905","DOIUrl":"https://doi.org/10.1109/PRECEDE51386.2021.9680905","url":null,"abstract":"The conventional model predictive control (MPC) strategy produce current errors when the parameters of the inverter mismatch, which increases the Total Harmonic Distortion of grid current. To solve this problem, an improved method based on Runge-Kutta algorithm (RKA) is proposed. On the basis of the mathematical model of grid- connected inverter, current error of parameters mismatch of conventional MPC is analyzed. Moreover, Lagrange interpolation is performed to achieve the predictive current instead of the slope parameters of RKA, because the uncertain model with detailed parameters affects the prediction accuracy. Finally, simulation results verify the accuracy and effectiveness of the improved RKA approach.","PeriodicalId":161011,"journal":{"name":"2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"4 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":"122088237","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
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