In this study, a speed estimation scheme using the fuzzy logic control (FLC) strategy adaptive flux estimator is presented for a direct stator field-orientation-controlled (DSFOC) induction motor (IM) drive. The current and flux of the stator were utilized to establish the DSFOC IM drive, and the stator current was obtained from the IM by utilizing Hall effect current sensors. The adaptive stator flux estimator was developed according to the voltagemodel and current-model stator flux estimators, and the estimated rotor speed was derived from this flux estimator. The adaptation mechanism of the adaptive stator flux estimator was designed using the FLC strategy. The synchronous position angle for the coordinate transformation between the stationary and synchronous reference coordinate frames was developed using the model reference adaptive system (MRAS) based on the reactive power of an IM. The MATLAB\Simulink ® toolbox was used to simulate this system, and all the control algorithms were realized using a 32-bit RX62T microcontroller to validate this approach. Both simulation and experimental results (including the estimated rotor speed, electromagnetic torque, and stator flux locus) confirmed the effectiveness of the proposed system and validated the proposed approach.
In this study, a coupled membrane-free microbial fuel cell (MFC) with permeable reactive barrier (PRB) was reported and its treatment performance and electricity generation for acid mine drainage (AMD) were examined. The pilot-scale continuous flow MFC-PRB was operated for five periods at a hydraulic retention time of 48.0 h, and the average sulphate removal percentages of 51.2%, 39.8%, and 33.1% were obtained in effluent of 1,000, 2,000, 3,000 mg/l, respectively. More than 99.5% of the initial concentrations of Cu 2+ , Zn 2+ , and Pb 2+ were removed, resulting in concentrations of those elements of 0.01-0.05 mg/l in the effluent. The results demonstrated that the MFC-PRB holds a potential capacity for remediation of AMD.
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