Model predictive control of high power converters and industrial drives

By Tobias Geyer. European Conference on Cognitive Ergonomics, 2016

267 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d3b11b05f9653024ef1366d62dc834159188774d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Petros P. Karamanakos
2. Tobias Geyer
3. Ralph M. Kennel
4. Eyke Liegmann
5. José Raúl Rodríguez Rodríguez
6. Yongchang Zhang

Citations in the corpus

• Algebraic Tuning Guidelines for Model Predictive Torque and Flux Control (2018, background): “The switch position at time step k with the minimum cost, uopt(k), is by definition the optimal one, see, for example, [1] and [26].”
• Model Predictive Control of Power Electronic Systems: Methods, Results, and Challenges (2020, background): “tion variable is a real-valued vector, then the solution to the unconstrained optimization problem can be easily found by setting the derivative of the objective function to zero [15].”
• Guidelines for the Design of Finite Control Set Model Predictive Controllers (2020, methodology): “In a last step, the optimal switch position is directly applied to the converter without an intermediate modulation stage [14].”