Nonlinear model predictive torque control and setpoint computation of induction machines for high performance applications

Englert T, Graichen K (2020)


Publication Type: Journal article

Publication year: 2020

Journal

Book Volume: 99

Article Number: 104415

DOI: 10.1016/j.conengprac.2020.104415

Abstract

This paper proposes a model predictive torque control scheme for induction machines. The approach utilizes an augmented Lagrangian method in combination with a tailored gradient algorithm to efficiently solve the optimal control problem. The problem formulation accounts for hexagonal voltage constraints as well as constraints on the phase currents and the DC link current. A tailored calculation scheme for energy-efficient current setpoints improves the performance and the stability of the approach. Experimental results with computation times of less than 100 μs on a DSPACE real-time platform prove the potential of the proposed torque control scheme.

Authors with CRIS profile

Involved external institutions

How to cite

APA:

Englert, T., & Graichen, K. (2020). Nonlinear model predictive torque control and setpoint computation of induction machines for high performance applications. Control Engineering Practice, 99. https://doi.org/10.1016/j.conengprac.2020.104415

MLA:

Englert, Tobias, and Knut Graichen. "Nonlinear model predictive torque control and setpoint computation of induction machines for high performance applications." Control Engineering Practice 99 (2020).

BibTeX: Download