State of the Art of Finite Control Set Model Predictive Control in Power Electronics
By José Raúl Rodríguez Rodríguez, Marian P. Kazmierkowski, José R. Espinoza, Pericle Zanchetta, Haitham Abu-Rub, Héctor A. Young, Christian A. Rojas. IEEE Transactions on Industrial Informatics, 2013
1,649 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/cb27a67002816efffdff8d8639577c99532db878
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
- Leopoldo García Franquelo
- Sergio Vazquez
- Ralph M. Kennel
- Xiaoguang Zhang
- Samir Kouro
- Petros P. Karamanakos
In Electrical and Electronic Engineering
- Tobias Geyer
- José Raúl Rodríguez Rodríguez
- Leopoldo García Franquelo
- Sergio Vazquez
- Samir Kouro
- Bin Wu
- Petros P. Karamanakos
- Marco E. Rivera
Citations in the corpus
- A Simplified Finite-Control-Set Model-Predictive Control for Power Converters (2014, background): “FCS-MPC has developed rapidly in the past few years, and studies on this topic have been spread out across various fields, for example, renewable energy, uninterruptible power supply (UPS) systems, and electric motor drivers [21]–[27].”
- Model Predictive Control for Power Converters and Drives: Advances and Trends (2017, methodology): “This has made it possible to implement more complex and intelligent control strategies, like MPC, in standard control hardware platforms [8]–[11].”
- Model Predictive Control for PMSM Drives With Variable Dead-Zone Time (2021, background): “3066636 However, the basic voltage vectors generated by the two-level inverter are finite, and only an optimal voltage vector is applied to the motor in a control period [12].”
- A Modified Double Vectors Model Predictive Torque Control of Permanent Magnet Synchronous Motor (2019, neutral): “2898901 control various object flexibly [4]–[6].”
- Model-Based Predictive Direct Control Strategies for Electrical Drives: An Experimental Evaluation of PTC and PCC Methods (2015, background): “The most advanced developments of predictive direct control for power electronics are clearly presented in [16].”
- Algebraic Tuning Guidelines for Model Predictive Torque and Flux Control (2018, background): “This tuning process is usually performed on a trial-and-error basis [2] and is thus considered an unresolved issue [3].”
- Finite Control Set Model Predictive Current Control for Grid-Connected Voltage-Source Converters With LCL Filters: A Study Based on Different State Feedbacks (2016, background): “2478862 predictive control algorithms [6]–[13] to be applied in industrial power electronic converter systems.”
- High-power wind energy conversion systems: State-of-the-art and emerging technologies (2015, methodology): “[266] J.”
- Guidelines for the Design of Finite Control Set Model Predictive Controllers (2020, background): “A common practice to keep the computational complexity at bay is to choose as short a prediction horizon as possible; in almost all cases, Np = 1 is selected [10].”
- Comprehensive Topological Overview of Rolling Stock Architectures and Recent Trends in Electric Railway Traction Systems (2017, background): “with inclusion of various constraints [100] is shown with a low horizon.”
- Finite-Control-Set Model Predictive Torque Control With a Deadbeat Solution for PMSM Drives (2015, positive): “The advantages of the FCS-MPTC method are its intuitive concept and straightforward implementation [4].”