Nonlinear model predictive torque control and setpoint computation of induction machines for high performance applications. (June 2020)

• Record Type: Journal Article
• Authors: Englert, Tobias; Graichen, Knut
• Is Part Of: Control engineering practice. Volume 99(2020)
• Publication Date: 2020-06
• Subjects: Induction machine -- Embedded optimization -- Augmented Lagrangian -- Nonlinear model predictive control -- Real-time implementation; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2020.104415
• Languages: English
• ISSNs: 0967-0661

Abstract

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 μ s on a d SPACE real-time platform prove the potential of the proposed torque control scheme.