Adequate output voltage control is essential in the integration of switched reluctance generators (SRGs) into wind energy conversion systems (WECS). In this regard, this paper proposes a discrete-time super-twisting sliding mode output voltage controller. The approach has a simple fixed-gain structure, not requiring model information or lookup tables on implementation. In order to overcome the complex task of parameter tuning, an optimization-based design approach is proposed, enabling a straightforward and systematic design stage. A two-term cost function is defined, seeking a balance between improved tracking performance and reduced chattering in the reference current value. Simulation results show the effectiveness of the proposal at output voltage regulation, while demonstrating robustness to different operating conditions.

The vibration/noise and torque ripple are two inherent issues for switched reluctance motors (SRMs), one of the effective methods to address these two issues is flattening both the total radial force and total torque. In this paper, an optimized quadratic-sharing-function-based radial force and torque simultaneous flattening method is proposed for SRMs. Firstly, the features of the radial force and torque characteristics are analyzed without considering saturation. Then, with these unique and specific features, four regions are defined to develop the simultaneous radial force and torque control method based on the linear sharing functions. To incorporate the saturation effects in the proposed method, the quadratic sharing functions are adopted. The proper parameters of the quadratic sharing functions and the region definition at different operating conditions are obtained through the genetic algorithm (GA) optimization. The switching angles and reference current of the conventional current chopping control (CCC) method are also optimized by GA for fair comparison purpose. Extensive simulation results are presented in this paper, and these results prove the effectiveness and superiority of the proposed method regarding the simultaneous radial force and torque control.

This paper presents a high frequency linear model for low-speed sensorless control of interior permanent magnet synchronous motor (IPMSM) drives. The proposed model uses a β-axis high frequency signal injection in order to model a new high frequency flux variable, which has similar properties to the standard electromotive force (EMF) used for high-speed sensorless control. Through the proposed model, the well established observer techniques from the literature can be used for rotor position and speed estimation. Thus, the low-speed sensorless scheme can be designed in similar form as the high-speed EMF based methods. Here, position and speed estimation are performed by an adaptive full-order observer, which is designed through a pole placement method and its stability constraints are investigated. Simulation results validate the proposed high frequency linear model and adaptive observer design method under sensorless vector control.

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Proper current control is essential in SRM drives in order to ensure adequate reference tracking and torque ripple reduction when using current profiling techniques. In this context, this paper proposes a PWM super-twisting sliding mode current controller for switched reluctance motors with a fixed-gain structure. The approach presents a model-free structure, not requiring model information on implementation. The PWM implementation ensures a fixed switching frequency and the fixed-gain approach leads to a simple control structure, not demanding any sort of gain lookup tables. The complex task of gain design for super-twisting controllers is solved in this paper by means of an optimization-based design methodology, using the sum of the squared error as a cost function. The proposed technique is compared to a higher sampling hysteresis controller in terms of current and torque root-mean-square error. Simulation results are presented, showing that the proposal achieves a performance comparable to a higher sampling hysteresis controller.

This paper proposes a procedure to optimize the firing angles of a switched reluctance generator via the particle swarm optimization algorithm. This aims to ensure performance with a balance between high energy efficiency and reduced torque ripple. The technique is intended for SRGs operating in the current-controlled region, below base speed. The proposed procedure is compared with a traditional fine grid approach in order to show the significant reduction in computational effort. Simulation results are provided, demonstrating that a performance with a balance between reduced torque ripple and increased efficiency is achieved.

This paper presents a rotor speed estimation technique based on a Luenberger observer for sensorless speed control of a synchronous reluctance motor (SynRM). The model of the SynRM is presented, both on the synchronous rotating frame as well as in the stationary rotating frame. The observer design is presented, along with the extended state space model, used to obtain both actual and observed αβ currents and αβ electromotive force (EMF). The field oriented control structure used in this paper is shown. Lastly, experimental results are presented in order to verify the effectiveness of the sensorless control strategy along with the convergence of the observed variables and estimated speed.

This paper presents the design of a sliding mode controller (SM) applied to the speed control of a switched reluctance motor. The SRM has a non-linear model, given its constructive nature and drive operation. The mathematical modeling is presented, taking into account the operation under saturation as well as a simplified model, where the inductance is considered only position dependent. The converter used to drive this machine is presented, as well as its principle of operation, dependent on the switching angles. Simulation and experimental results are presented in order to demonstrate the effectiveness of the proposed control strategy.