Iterative learning control based direct instantaneous torque control of switched reluctance motors

In this paper, iterative learning control (ILC) based direct instantaneous torque controller (DITC) for SRM is proposed. Direct torque control avoids the conversion of demanded motor torque into equivalent phase current references; which is non-trivial due to the coupled and non-linear torque, current and rotor position relationship. The instantaneous torque controller is capable of minimizing SRM torque ripples in addition to accurate average torque control. Torque ripples are intolerable for many high performance applications, especially at low speeds. The proposed controller uses a sliding mode controller (SMC) combined with ILC for accurate torque tracking. ILC is effective in minimizing torque ripples during steady state operations. Due to the finite time required for ILC learning, there is performance degradation during transient periods. The paper shows the design of an SMC for improving control performance during transient periods as well. Unlike the case of sliding mode controller alone, where a high gain switching control is added to the model-based equivalent control; ILC iteratively learns and compensates for any model inaccuracy. Thus the proposed scheme does not require an accurate plant model, but at the same time, makes use of any available plant knowledge in improving torque control performance. Experimental results are provided which show the effectiveness of the proposed DITC scheme.