# An Improved Hybrid Control Scheme of a Switched Reluctance Motor for Torque Ripple Reduction
## 1 Introduction  
Switched reluctance motors (SRMs), with a simple structure, low manufacturing cost, and strong robustness, have been extensively studied [1; 2; 3]. However, owing to their double salient structure and nonlinear magnetic characteristics, the torque ripple is larger in SRMs than other motors, such as permanent magnet motors and induction motors, especially in the commutation interval. Therefore, a number of approaches regarding torque ripple suppression have been proposed, such as design, optimization, modeling, and control [4; 5; 6]. In terms of the control scheme, a basic control strategy and an advanced control algorithm are the two main research directions [7; 8; 9]. Popular control strategies in recent years can be classified as torque sharing function (TSF), current profiling, direct instantaneous torque control, direct torque control, and model predictive control (MPC) [10; 11; 12]. Among them, TSF allocates the desired torque to each phase; thus, the resultant instantaneous torque can track the desired torque produced by the controller [13; 14]. Related improvement studies with respect to functional expression and optimization have been presented. In terms of functional design, for instance, an offline TSF [15], a TSF with a nonlinear modulating factor [16], and a TSF based on dynamic allocation [17] have been proposed to reduce the torque ripple and copper loss. Furthermore, approaches involving compensating current and torque error have been introduced to obtain improved torque performance [18; 19]. As another direction on the optimization procedure, related studies on comprehensive performance have also been presented, such as objective functions considering current and the rate of change of current [20; 21; 22]. For constraints and multivariable systems, MPC is an alternative method that predicts the future output value according to the current state quantity [23]. The future values,including current, torque, and flux linkage, can be predicted according to the model. Then, the construction of cost function is established to select the appropriate operation mode. The technique involves online correction and rolling optimization of the model according to feedback information. In [12; 24], a virtual space vector modulation and a novel switching table were established to suppress the torque ripple, achieve high efficiency, and reduce the computational burden. In recent works, MPC was combined with other strategies to further improve the performance. For instance, MPC was integrated with DTC to achieve desired performances, such as elimination of negative torque [25]. Similarly, the combination of TSF and MPC can effectively suppress the torque ripple and avoid the frequency conversion caused by hysteresis control [26; 27; 28]. Moreover, several control techniques, i.e., adaptive control, deadbeat control, and current profiling, were incorporated with MPC to achieve performances such strong anti-disturbance ability, fixed switching frequency, low torque ripple, and an extended speed range [29; 30]. Aside from the multiple control strategy, a variety of control algorithms have been successfully applied to the design of speed controllers for performance improvement. Sliding mode control, adaptive control, active disturbance rejection control (ADRC), and fuzzy control all exhibit considerable potential significance [31; 32; 33]. As a common control algorithm, ADRC performs well in speed tracking, adaptability, and anti-disturbance ability [34; 35]. In [36], a high-gain nonlinear error decay function based on ADRC was presented to enhance performance during starting operation. Aside from nonlinear ADRC, linear ADRC (LADRC) has been applied in various engineering applications, owing to its fewer tunable parameters. For instance, a class of linear-nonlinear switching ADRC [37] and several advanced LADRCs [38] were designed for strong anti-disturbance ability, the speed of the observer, and position estimation performance, respectively.