S. Hanke, Sebastian Peitz, O. Wallscheid, J. Böcker, M. Dellnitz
{"title":"Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification","authors":"S. Hanke, Sebastian Peitz, O. Wallscheid, J. Böcker, M. Dellnitz","doi":"10.1109/PRECEDE.2019.8753313","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753313","url":null,"abstract":"In comparison to classical control approaches in the field of electrical drives like the field-oriented control (FOC), model predictive control (MPC) approaches are able to provide a higher control performance. This refers to shorter settling times, lower overshoots, and a better decoupling of control variables in case of multi-variable controls. However, this can only be achieved if the used prediction model covers the actual behavior of the plant sufficiently well. In case of model deviations, the performance utilizing MPC remains below its potential. This results in effects like increased current ripple or steady state setpoint deviations. In order to achieve a high control performance, it is therefore necessary to adapt the model to the real plant behavior. When using an online system identification, a less accurate model is sufficient for commissioning of the drive system. In this paper, the combination of a finite-control-set MPC (FCS-MPC) with a system identification is proposed. The method does not require high-frequency signal injection, but uses the measured values already required for the FCS-MPC. An evaluation of the least squares-based identification on a laboratory test bench showed that the model accuracy and thus the control performance could be improved by an online update of the prediction models.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134623019","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}
{"title":"Three-Vector Model Predictive Current Control of Permanent Magnet Synchronous Motor Based on SVM","authors":"Hongmin Lin, Wenxiang Song","doi":"10.1109/PRECEDE.2019.8753364","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753364","url":null,"abstract":"Aiming at the problem that the conventional model predictive current control (MPCC) of permanent magnet synchronous motor (PMSM) fed by two level voltage-source inverter (VSI) applies only one voltage vector during a control period, which makes the stator current tracking control over-regulated or under-regulated, a three-vector model predictive current control algorithm based on space vector modulation (SVM) is investigated in this paper. The principle of SVM, the parallelogram law, is adopted to synthesize the expected voltage vector with two adjacent active vectors, so that the expected voltage vector can cover any phases and amplitudes. The durations of the basic voltage vectors are calculated by the principle of deadbeat current control. The time delay caused by the computing time will cause the stator current to oscillate around its reference and increase the torque ripples. To address this, the delay compensation method is employed to improve the control performance of the system. The validity and feasibility of the proposed method is verified by the comparative researches of simulation modeling.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114490426","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}
Yongdu Wang, Zhenbin Zhang, Weiqing Huang, R. Kennel, W. Xie, Fengxiang Wang
{"title":"Encoderless Sequential Predictive Torque Control with SMO of 3L-NPC Converter-fed Induction Motor Drives for Electrical Car Applications","authors":"Yongdu Wang, Zhenbin Zhang, Weiqing Huang, R. Kennel, W. Xie, Fengxiang Wang","doi":"10.1109/PRECEDE.2019.8753238","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753238","url":null,"abstract":"Finite control set predictive torque control (FCSPTC) is well-known for its fast response and good flexibility. However, drawbacks such as speed dependence and tedious tuning efforts for weighting factors lead to system failure and implementation complexity. This work proposes a revised FCSPTC method for 3L-NPC converter-fed induction motor (IM) using a sliding mode observer (SMO) to estimate the speed errors caused by the rotor shaft encoder. The novelty lies in two aspects: I. The revised SMO frees the controller from the speed signal dependence, eliminating potential accumulated errors from the speed feedback channels. II. The cost function is realized with a sequential structure, avoiding tedious tuning efforts for weighting factors design. Theoretical analysis and simulation results reveal that: the proposed control scheme performs well without weighting factors and achieves encoderless torque control at both transient and steady-state operation phases.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124910122","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}
{"title":"Improved Predictive Current Control of IM Drives Based on a Sliding Mode Observer","authors":"Haitao Yang, Yongchang Zhang, Peng Huang","doi":"10.1109/PRECEDE.2019.8753274","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753274","url":null,"abstract":"In the conventional finite control set-model predictive current control (FCS-MPCC) method, both stator current and flux-linkage vector need to be computed for delay compensation and coordinate transformation. And, the conventional PCC is sensitive to rotor parameter mismatches. Additionally, the performance of FCS-MPCC degrades during speed variation when low-pass filter is applied to attenuate noise in speed measurement. In this paper, a reduced-order sliding-mode current observer (RSCO) is designed, which can predict stator current at the next sampling instant while simultaneously estimating the back electromotive force. With the help of RSCO, current prediction and coordinate transformation can be achieved without calculation of flux-linkage vector, which features simplicity in practical application. Additionally, robustness against parameter mismatch is significantly improved due to the feedback of current estimation error. Simulation and experimental results are presented to validate effectiveness of the proposed method.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127809733","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}
M. Rossi, E. Liegmann, P. Karamanakos, F. Castelli-Dezza, R. Kennel
{"title":"Direct Model Predictive Power Control of a Series-Connected Modular Rectifier","authors":"M. Rossi, E. Liegmann, P. Karamanakos, F. Castelli-Dezza, R. Kennel","doi":"10.1109/PRECEDE.2019.8753318","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753318","url":null,"abstract":"This paper presents a direct model predictive power control for a series-connected modular rectifier. The topology combines a diode rectifier and an active-front-end (AFE) converter to achieve a medium voltage target. A voltage control loop regulates the total dc voltage, providing the power references to the inner direct model predictive control. Operation under the desired real and reactive power is achieved, while minimizing the converter switching frequency. Moreover, successful operation and control of the AFE converter is guaranteed thanks to a hard constraint included in the optimization problem.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128763657","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}
{"title":"Predictive control with variable amplitude of voltage vector of interior PMSM direct torque control system","authors":"Yao-hua Li, Jiayue Ren, Qidong Yang","doi":"10.1109/PRECEDE.2019.8753367","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753367","url":null,"abstract":"Based on stator flux and torque's expressions of interior permanent magnet synchronous motor (PMSM) direct torque control (DTC) system in stator flux frame, voltage vector with variable amplitude and fixed angle is used as candidate output voltage vector. The amplitude of stator flux and torque at next sampling point after applying voltage vector with different amplitude are obtained. A one-step selection algorithm is established based on the cost function of stator flux and torque's errors, which can choose voltage vector to minimize the cost function. More candidate voltage vectors will lead to better control performance, but it will cause heavier calculation burden. In this paper, control performances of interior PMSM DTC system are compared using 10 different methods to divide voltage vector. Considering control performance and calculation burden, dividing voltage vector into five equal parts to get the aggravate of 5 candidate voltage vectors is an ideal way. And system performance tends to be stable.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123748228","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}
{"title":"Model Predictive Control of Grid-Connected Power Converters with LCL Filter and Additional Feedback","authors":"P. Falkowski","doi":"10.1109/PRECEDE.2019.8753273","DOIUrl":"https://doi.org/10.1109/PRECEDE.2019.8753273","url":null,"abstract":"The benefits of using LCL filter connecting the grid with converter heavily depends on control method. Researchers in field of predictive control are mainly focused on improved the response dynamics, stability and accuracy of reference current tracking. This paper introduces an extended predictive control scheme of power converter with an LCL filter with improved operation under grid distortions. The proposed modification of control algorithm uses additional feedback form grid current to increase robustness for higher harmonics in grid voltage. The simulation results have proven good performance and verified the validity of the proposed solution. The laboratory test setup provided experimental results showing properties of the described method.","PeriodicalId":227885,"journal":{"name":"2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128497210","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}