2011 Workshop on Predictive Control of Electrical Drives and Power Electronics最新文献

{"title":"Finite-set model predictive control of the two-mass-system","authors":"Esteban J. Fuentes, R. Kennel","doi":"10.1109/PRECEDE.2011.6078734","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078734","url":null,"abstract":"This paper presents the design of a control scheme for the two-mass-system based on the Finite-Set Model Predictive Control method. The whole system state is controlled in a centralized way, so that the problem is solved more holistically, that is to say, using all degrees of freedom available. Constraints in the prediction horizon, given by the limited computation power and speed of the system dynamics, and the consequent myopic perspective of the controller, are solved by means of an ad-hoc cost function. The control is done using measurements of the stator currents and the speed of the driving machine. The rest of the system state is estimated using a Kalman Filter.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129644657","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":"Heuristic multi-objective optimization for cost function weights selection in finite states model predictive control","authors":"P. Zanchetta","doi":"10.1109/PRECEDE.2011.6078690","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078690","url":null,"abstract":"This research work investigates an automated and optimal procedure for the selection of the cost function weights in Finite States Model Predictive Control (FS-MPC). This is particularly useful where the cost function is composed by more variables and where other control parameters need to be carefully designed. A Genetic Algorithm (GA) multi-objective optimization approach is here proposed and tested on a case study represented by the FS-MPC of a Shunt Active Power Filter (SAF). The results of this weights optimization procedure are reported and discussed with the aid of Matlab-Simulink simulation tests.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125755402","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":"FPGA implementation of online finite-set model based predictive control for power electronics","authors":"S. Thielemans, T. Vyncke, M. Jacxsens, J. Melkebeek","doi":"10.1109/PRECEDE.2011.6079085","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6079085","url":null,"abstract":"Recently there has been an increase in the use of model based predictive control (MBPC) for power-electronic converters. MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. The computational burden for this control scheme however is very high and often restrictive for a good implementation. This means that a suitable technology and design approach should be used. In this paper the implementation of finite-set MBPC (FS-MBPC) in field-programmable gate arrays (FPGAs) is discussed. The control is fully implemented in programmable digital logic by using a high-level design tool. This allows to obtain very good performances (both in control quality, speed and hardware utilization) and have a flexible, modular control configuration. The feasibility and performance of the FPGA implementation of FS-MBPC is discussed in this paper for a 4-level flying-capacitor converter (FCC). This is an interesting application as FS-MBPC allows the simultaneous control of the output current and the capacitor voltages, yet the high number of possible switch states results in a high computational load. The good performance is obtained by exploiting the FPGA's strong points: parallelism and pipe-lining. In the application discussed in this paper the parallel processing for the three converter phases and a fully pipelined calculation of the prediction stage allow to realize an area-time efficient implementation.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129152390","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":"Design choices for the prediction and optimization stage of finite-set model based predictive control","authors":"T. Vyncke, S. Thielemans, T. Dierickx, R. Dewitte, M. Jacxsens, J. Melkebeek","doi":"10.1109/PRECEDE.2011.6078687","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078687","url":null,"abstract":"The interest in applying model-based predictive control (MBPC) for power-electronic converters has grown tremendously in the past years. This is due to the fact that MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. As MBPC is a family of possible controllers rather than one single controller, several design choices are to be made when implementing MBPC. In this paper several conceptual possibilities are considered and compared for two important parts of online Finite-Set MBPC (FS-MBPC) algorithm: the cost function in the optimizations step and the prediction model in the prediction step. These possibilities are studied for two different applications of FS-MBPC for power electronics. The cost function is studied in the application of output current and capacitor voltage control of a 3-level flying-capacitor inverter. The aspect of the prediction model is studied for the stator flux and torque control of an induction machine with a 2-level inverter. The two different applications illustrate the versatility of FS-MBPC. In the study concerning the cost function firstly the comparison is made between quadratic and absolute value terms in the cost function. Comparable results are obtained, but a lower resource usage is obtained for the absolute value cost function. Secondly a capacitor voltage tracking control is compared to a control where the capacitor voltage may deviate without cost from the reference up to a certain voltage. The relaxed cost function results in better performance. For the prediction model both a classical, parametric machine model and a back propagation artificial neural network are applied. Both are shown to be capable of a good control quality, the neural network version is much more versatile but has a higher computational burden. However, the number of neurons in the hidden layer should be suffciently high. All studied aspects were verified with experimental results and these validate the simulation results. Even more important is the fact that these experiments prove the feasibility of implementing online finite-set MBPC in an FPGA for both applications.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134199316","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 torque control of an induction machine fed by a neutral point clamped inverter","authors":"P. Stolze, F. Bauer, Peter Landsmaan, R. Kennel, Toit Moutonl","doi":"10.1109/PRECEDE.2011.6078683","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078683","url":null,"abstract":"This paper presents a model predictive control strategy for an induction machine fed by a three-level neutral point clamped inverter. Two different voltage balancing algorithms are compared: The first one is hysteresis-based, the second algorithm is weighting factor-based, i. e. the DC link capacitor voltage unbalance is evaluated directly within the cost function. The proposed control algorithms are verified by several simulations which clearly verify that an effective control of speed, torque, flux and of the DC link capacitor voltages is possible.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115273901","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":"Hierarchical direct predictive control of PMSM drives","authors":"M. Carraro, M. Zigliotto","doi":"10.1109/PRECEDE.2011.6078680","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078680","url":null,"abstract":"The paper deals with a Direct Predictive Control (DPC) algorithm applied to the speed and current control of a permanent magnet synchronous motor (PMSM) drive. The main contribution is a comprehensive and detailed description of the hierarchical structure, which yields a choice of the control input voltage that combines dynamic performances with the efficiency care. The selection principle is particularly simple and intuitive, and thus it is suitable for direct implementation in standard drives. The paper also gives some practical hints for the implementation. Simulation and experimental results confirm the validity of the design procedure and the potentiality of the proposed technique.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134220330","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 a three-to-five phase matrix converter","authors":"S. Ahmed, A. Iqbal, H. Abu-Rub, P. Cortes","doi":"10.1109/PRECEDE.2011.6078685","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078685","url":null,"abstract":"The paper proposes model predictive control strategy to control active and reactive power simultaneously in addition to the source and load current using predictive approach for a three-phase input to five-phase output matrix converter. The proposed method selects the actuation states of the matrix converter according to the optimization algorithm of the cost function. The proposed cost function considers the active and reactive input power control to facilitate the control of source side power factor. Additionally source and load side currents are controlled to be sinusoidal. The proposed control approach offer good tracking of the reference and actual source and load current and can control the source side power factor to any value. The analytical and simulation approach is adopted in the paper.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115547737","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 VSS switching control of a three-phase inverter","authors":"K. Jezernik, R. Horvat","doi":"10.1109/PRECEDE.2011.6078686","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078686","url":null,"abstract":"A novel predictive VSS switching based current controller for three-phase load driven by power inverter is proposed. Main design specifications are robustness to load electrical parameters, fast dynamic response, reduced switching frequency and simple hardware implementation. To meet previous specifications a switching two types of switching controllers are developed: hysteresis type and predictive type. The voltage source inverter (VSI) is represented as event driven system with 23 modes of operation. The switching among these modes is governed by the supervisory control approach. The regulation with the proposed control law provides good transient response of the brushless BLDC motor control. A new logical FPGA torque and speed controller is developed, analyzed and experimentally verified.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128290086","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":"A switching model predictive control for overcoming a hysteresis effect in a hybrid actuator for camless internal combustion engines","authors":"Paolo Mercorelli","doi":"10.1109/PRECEDE.2011.6078681","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078681","url":null,"abstract":"This paper deals with a hybrid actuator composed by a piezo and a hydraulic part and with a switching Model Predictive Control (MPC) Structure for camless engine motor applications. In a precision control problem, nonlinearities such as hysteresis, creep etc. must be taken into account. In this paper the Preisach dynamic model with the above mentioned hysteresis is considered together with a robust switching MPC utilized to manage the hysteresis nonlinearity. Simulations with real data are shown.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127588133","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":"The polynomial approximation of the explicit solution of model-based predictive controller for drive applications","authors":"N. A. Ameen, B. Galal, R. Kennel, R. Kanchan","doi":"10.1109/PRECEDE.2011.6078733","DOIUrl":"https://doi.org/10.1109/PRECEDE.2011.6078733","url":null,"abstract":"The complexity of implementing the Explicit solution of Model-based Predictive Control (Exp-MPC) in drive applications results in a higher number of generated regions. This increases the required memory space to store these regions and the coefficients of the associated optimal control laws, even when the solution is implemented using an efficient algorithm like Binary Search Tree (BST). The proposed method aims to replace the optimal linear/affine control laws, defined over several regions of the feasible state space, with one polynomial. The polynomial will be multivariate, with higher order, and defined over a combination of feasible regions. Using the polynomial approximation, the necessary memory space, to store region coordinates and the coefficients of optimal control laws, is reduced significantly. Although the accuracy of the optimal controller is reduced with use of polynomial approximation, it makes the implementation more realistic; provided the stability and the feasibility of the problem is still guaranteed.","PeriodicalId":406910,"journal":{"name":"2011 Workshop on Predictive Control of Electrical Drives and Power Electronics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116180855","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}