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The aim of this study is to introduce the maximum torque per total ampere (MTPTA) control strategy for brushless doubly fed induction machine drives taking iron loss into account. In this regard, the condition for realizing the MTPTA is investigated in the presence of iron loss by a theoretical approach. It is shown the proposed strategy is realized when the MTPTA criterion tracks zero as reference signal. As a result, the current is not only shared between the stator windings fairly but also total stator currents are minimized for a given torque. The experimental results confirm the performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article proposes a new ripple canceling circuit (RCC) to eliminate the pulsating input current of the conventional flyback converter (CFC). The ripple canceling procedure occurs by two capacitors, one transformer, and a winding, which is added to the CFC transformer core. Besides, the proposed RCC acts as a passive snubber to reduce voltage spikes on the power switch of the converter. In comparison to the similar existing topologies, the proposed RCC does not employ additional semiconductors, and a lower number of magnetic components are used. The proposed RCC is verified by simulation and experimental results. The results show that using the proposed RCC, the input current ripple is reduced to 6% with the minimum power losses. [ABSTRACT FROM AUTHOR]

This paper proposes a direct speed and flux control system for Dual Stator Winding Induction Machines (DSWIMs) based on Super Twisting Sliding Mode Control (STSMC). The proposed nonlinear controller which has finite time convergence of error to zero, is designed such that the Lyapunov stability condition is satisfied. Furthermore, a novel torque-sharing algorithm is introduced for DSWIMs. This algorithm enables them to operate in a wide speed region, including zero speed, such that the required electromagnetic torque is supplied by two winding sets based on their power ratings. In addition, a Sliding Mode Control (SMC) based full order observer is proposed for DSWIMs. This observer, which is able to estimate the winding fluxes, flux angles and rotor speed with high-accuracy, guarantees the optimal flux condition. The functionality of the proposed sensor-less DSWIM drive scheme is evaluated through some experimental tests performed on a 3.3 kW DSP-based DSWIM drive system. The experimental results confirm the effectiveness of the proposed control method, torque sharing algorithm and the full order observer in various speed regions. [ABSTRACT FROM AUTHOR]

This article proposes a nonlinear controller for brushless doubly-fed induction motor (BDFIM) drives on the basis of input–output feedback linearization (IOFL). In the proposed control approach, first, the maximum torque per inverter ampere (MTPIA) control strategy is considered by applying a fifth-order (reduced-order) model of BDFIM. By realizing the MTPIA, the control winding (CW) current magnitude is minimized under the constraint of constant torque. The realization criterion of MTPIA approach is independent of torque level and CW frequency. To fairly share the current between stator windings and minimizing the total current magnitude for a given torque, the MTPIA idea should be extended. Since, the power winding (PW) of BDFIM is not controllable, obtaining this purpose is a challenge. Therefore, to solve this problem, the model-based maximum torque per total ampere (MTPTA) control is introduced for BDFIM drives and the conditions for realizing this strategy are determined. It should be noted that the total amperes refer to the sum of the PW and the CW current magnitudes. In addition, using the fifth-order model of BDFIM, a nonlinear controller is developed based on IOFL technique which is capable to force the deviation from realization criterion of both proposed strategies to zero while the torque is controlled with high accuracy. The overall stability of the proposed controller is proven using the Lyapunov control theory. The validity of the proposed approach is finally verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

Dual stator winding induction machines (DSWIMs), which have two sets of three-phase windings with unequal pole pairs in their stator and a standard squirrel cage rotor, have overcame the narrow speed operation region and circulating current problems exists in other types of dual winding machines. These advantages are resulted from the independent operation of their winding sets. The independent operation of winding sets will be guaranteed if the flux saturation is avoided. This letter proposes a novel reference frame angle determination technique that not only guarantees the flux saturation avoidance but also results in flux optimization in DSWIMs. Despite pervious methods, the proposed method does not require position or speed sensor and it is easily applicable in various control schemes and in different reference frames. This method is implemented in a flux and torque vector control system for driving a 3.3 kW DSWIM. The experimental results confirm the effectiveness of the proposed method. Moreover, by implementing the proposed method, the torque sharing between the two winding sets is properly done according to the power rating of each of them. [ABSTRACT FROM AUTHOR]

In this paper, speed and torque control modes (SCM and TCM) of synchronous reluctance motor (SynRM) drives are proposed based on emotional controllers and space vector modulation under an automatic search of the maximum-torque-per-ampere (MTPA) strategy. Furthermore, in order to achieve an MTPA strategy at any operating condition, after recognition of transient state by two new indicators, a search algorithm changes the stator flux magnitude automatically. The indicators operate based on slip effect generated at transient conditions in a SynRM with cage. The performance of the proposed controller is compared with an optimized conventional PI controller under different operating conditions. Simulation and experimental results demonstrate the benefits of the proposed approach. This structure shows superiority of the proposed method, such as fast dynamic, simple implementation and robustness to parameter variations and external disturbances in both TCM and SCM. In addition, the proposed MTPA strategy shows a reliable and fast response to operating point change. [ABSTRACT FROM AUTHOR]

In this paper, a well-known adaptive input-output feedback-linearization (AIOFL) technique is used for speed and torque-tracking control of synchronous reluctance motor drive. This controller is capable of estimating motor two-axis inductances (Ld, Lq) simultaneously. The overall stability of the proposed control and the persistency of excitation condition are proved based on Lyapunov theory. In addition, the maximum rate of change of torque control scheme is applied to generate the motor dand q-axis reference currents which are needed for AIOFL controllers. Another contribution of this paper is to estimate the rotor speed and position. For low-speed estimation, we have to eliminate the current and voltage sensors' dc offsets, detect the stator resistance, and take into account the voltage drop of the inverter power switches. We solve these problems by using a simple technique for eliminating the voltage sensors and a simple method for online estimation of the stator resistance and modeling the voltage drop of the inverter power switches. It is worthwhile to mention that the current sensors' dc offsets, seen on the measured currents, are negligible. Finally, the validity of the proposed method is verified by experimental results. [ABSTRACT FROM AUTHOR]

Control issue in electrical drives mainly deals with the dynamic behavior, which is based on the deviation of variables. The deviations play a straightforward role in presenting the various capabilities and merits of the electric drive systems. This paper describes, for the first time, a deviation-based torque control of synchronous reluctance motor (SynRM) drives with no need to know the motor parameters. The proposed control system is designed by using a normalized deviation model to derive linear and simple relationships amongst different machine signals. Therefore, the commonly used proportional–integral current regulators are replaced by novel deviation equations. As a result, the proposed approach provides facilities to electric drives, including control system simplicity, parameter independency, and no need for controller tuning. The theoretical findings are verified by those experiments. The obtained results are reported for a typical SynRM drive. In addition, performance comparison of the control system with a general PI controller-based field-oriented control scheme is carried out. It is expected that the proposed approach contributes to other electrical drives to simplify the machine equations, reduce control complexities, such as the number of conventional controllers, and overcome the problem of machine parameter dependency. [ABSTRACT FROM AUTHOR]

This paper proposes an enhanced brain emotional learning-based intelligent controller for synchronous reluctance motor (SynRM) drives. The controller is based on an emotional learning and decision making mechanism in the brain via emotional cues and sensory inputs. Furthermore, the enhanced controller improves learning process in the amygdala to avoid internal instability. In spite of the development for interior-stability, the proposed controller could keep its ability to deal with challenges related to SynRM drives. The proposed controller is also contributed with a speed deviation control. The new deviation controller is based on model but parameter-free. The updated system is implemented in real-time by a PC-based three-phase 370 W laboratory SynRM. The proportional-integral (PI) controllers used in a standard rotor field-oriented control structure are replaced with those of the proposed method. The speed and d-axis stator current references are accurately tracked. The achieved performances by the proposed controllers are compared with those of optimized conventional PI controller in different situations. Considering the results, the enhanced system shows superiority over the traditional system in terms of fast dynamics, easy tuning, and robustness against disturbances and parameter variations. [ABSTRACT FROM AUTHOR]