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Model predictive torque control of a Switched Reluctance Motor

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3 Author(s)
Peyrl, H. ; Autom. Control Lab., ETH Zurich, Zurich ; Papafotiou, G. ; Morari, M.

The strongly nonlinear magnetic characteristic of switched reluctance motors (SRMs) makes their torque control a challenging task. In contrast to standard current-based control schemes, we use model predictive control (MPC) and directly manipulate the switches of the dc-link power converter. At each sampling time a constrained finite-time optimal control problem based on a discrete-time nonlinear prediction model is solved yielding a receding horizon control strategy. The control objective is torque regulation while winding currents and converter switching frequency are minimized. Simulations demonstrate that a good closed-loop performance is achieved already for short prediction horizons indicating the high potential of MPC in the control of SRMs.

Published in:

Industrial Technology, 2009. ICIT 2009. IEEE International Conference on

Date of Conference:

10-13 Feb. 2009