Predictive Current Control of a Voltage Source Inverter
By José Raúl Rodríguez Rodríguez, Jorge A. Pontt, César A. Silva, Pablo Correa, P. Lezana, Patricio Cortes, Ulrich Ammann. IEEE transactions on industrial electronics (1982. Print), 2004
1,587 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/c1718fb990907c2a95228ce8cc8911c37222c4be
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Tobias Geyer
- José Raúl Rodríguez Rodríguez
- Tomislav Dragicevic
- Yongchang Zhang
- Mateja Novak
- Christian A. Rojas
- José R. Espinoza
- Patricio Cortes
In Electrical and Electronic Engineering
- Tobias Geyer
- José Raúl Rodríguez Rodríguez
- Yongchang Zhang
- Leopoldo García Franquelo
- Patricio Cortes
- Samir Kouro
- Tomislav Dragicevic
- Sergio Vazquez
Citations in the corpus
- Control of HVDC Light System Using Conventional and Direct Current Vector Control Approaches (2010, positive): “development of the proposed control mechanism has also been based on predictive current control (PCC) notions [39]–[41].”
- Model predictive control of high power converters and industrial drives (2016, methodology): “Predictive current control with reference tracking, however, was originally proposed with the 1-norm, or in other words, the sum of the absolute values of the current error components [2].”
- Model-Free Predictive Current Control for Interior Permanent-Magnet Synchronous Motor Drives Based on Current Difference Detection Technique (2014, methodology): “Similar to the MBPCC [11], [12], the next switching state that minimizes a cost function can be determined at the present sampling time and then to directly trigger the inverter in the next sampling interval.”
- Model Predictive Control for Power Converters and Drives: Advances and Trends (2017, methodology): “References [13], [14] [15], [16] [17], [18] [19], [20]”
- Guidelines for the Design of Finite Control Set Model Predictive Controllers (2020, methodology): “The optimization problem (10) is often solved by using the brute-force approach of exhaustive enumeration [8].”
- Latest Advances of Model Predictive Control in Electrical Drives—Part II: Applications and Benchmarking With Classical Control Methods (2021, background): “is considered, the cost function should be evaluated for the set of possible voltage vectors [59]–[61].”
- Imposed Sinusoidal Source and Load Currents for an Indirect Matrix Converter (2012, background): “As demonstrated in [3] and [15], the high calculation power of today’s existing digital signal processors (DSPs) makes this method very attractive to control power converters.”
- Vector control of single-phase voltage source converters based on Fictive Axis Emulation (2009, background): “During the last years, considerable research has been conducted on the current regulation of VSCs, and various approaches have been proposed [6-11].”
- Medium-Voltage Multilevel Converters—State of the Art, Challenges, and Requirements in Industrial Applications (2010, methodology): “Other techniques like direct torque control, hysteresis current control, and predictive control are also used for MLIs [19], [25], [114], [116]–[122], [157], [158].”
- Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach (2019, methodology): “The predicted numerical values of converter’s state variables at the next sampling step are then used in the cost function that defines the desired performance of the system [4].”
- Predictive Control of a Three-Phase Neutral-Point-Clamped Inverter (2007, methodology): “In [21] and [ 22 ], a new variant of MPC is used to control a matrix converter and a three-phase twolevel inverter, respectively.”
- Predictive Current Control With Input Filter Resonance Mitigation for a Direct Matrix Converter (2011, methodology): “Additionally, is [k + 2] and io [k + 2] are obtained using the system dynamic at the next sampling time (10)–(12), while the predictions of the source voltages vs [k + 1] and vs [k + 2] are obtained throughout a Lagrange interpolation expressed in (19) and (20), respectively [8].”
- High-Performance Control Strategies for Electrical Drives: An Experimental Assessment (2012, methodology): “Hence, the predictive algorithm is applied as in (15), but shifted one a sample step to predict ̂ ψs(k + 2) and T̂ (k + 2) [17].”
- Explicit Model-Predictive Control of a PWM Inverter With an LCL Filter (2009, background): “All possible switch combinations are considered and evaluated at each sampling instant [14].”
- Advanced Power Electronic Conversion and Control System for Universal and Flexible Power Management (2011, background): “Finally, a natural reference frame is normally used with hysteresis [25] or predictive [26]–[28] controllers that give very fast response and are particularly suitable for microprocessor implementation [29].”
- A Simplified Finite-Control-Set Model-Predictive Control for Power Converters (2014, methodology): “To achieve the same current waveform quality, the control loop cycle time of FCS-MPC should be much shorter than that of the conventional linear control methods [28], [29].”