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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 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]