The presence of an integrator in a reference model of a rotor flux-based model reference adaptive system(RF-MRAS)and non-linearity of the inverter in the output voltage degrade the speed response of the sensorless ope...The presence of an integrator in a reference model of a rotor flux-based model reference adaptive system(RF-MRAS)and non-linearity of the inverter in the output voltage degrade the speed response of the sensorless operation of the electric drive system in terms of DC drift,initial value issues,and inaccurate voltage acquisition.To improve the speed response,a compensating voltage component is supplemented by an amending integrator.The compensating voltage is a coalition of drift and offset voltages,and reduces DC drift and initial value issues.During low-speed operation,inaccurate voltage acquisition distorts the stator voltage critically,and it becomes considerable when the stator voltage of the machine is low.Implementing a three-level neutral point clamped inverter in speed-sensorless decoupled control of an induction motor improves the performance of the drive with superior quality of inverter output voltage.Further,the performance of the induction motor drive is improved by replacing the proportional-integral(PI)controller in the adaption mechanism of RF-MRAS with an adaptive neuro-fuzzy inference system(ANFIS)controller.A prototype model of the three-level neutral point clamped inverter(3L-NPC)-fed induction motor drive is fabricated in a laboratory,and its performance for a RF-MRAS,modified RFMRAS,and modified RFMRAS using ANFIS are compared using different benchmark tests.展开更多
Model reference adaptive system(MRAS)is typically employed for rotor position/speed estimation in sensorless interior permanent magnet motor(IPMSM)drives.The adjustment of control parameters in MRAS is a key issue for...Model reference adaptive system(MRAS)is typically employed for rotor position/speed estimation in sensorless interior permanent magnet motor(IPMSM)drives.The adjustment of control parameters in MRAS is a key issue for IPMSM drive systems with cyclic fluctuating loads.In order to avoid the difficulties involved with manual tuning of the control parameters,a new MRAS scheme based on fuzzy logic is proposed in this paper in which a fuzzy controller replaces the conventional PI regulator.To implement this new MRAS scheme,a two-dimensional(2-D)fuzzy rule is designed.The proposed control scheme is employed in the IPMSM drives with cyclic fluctuating loads such as compressors.In order to lower the motor speed ripple caused by the cyclic fluctuating load,a feed-forward compensation strategy with the load-matching motor output torque pattern is developed.Experimental results demonstrate the feasibility and effectiveness of the proposed fuzzy logic based MRAS scheme with minimal rotor position estimation error.展开更多
In this paper a fuzzy logic （FL） based model reference adaptive system （MRAS） speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from th...In this paper a fuzzy logic （FL） based model reference adaptive system （MRAS） speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller （FLC） for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic （PV） energy source is used. To extract the maximum power from the PV source, a constant voltage controller （CVC） is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.展开更多
文摘The presence of an integrator in a reference model of a rotor flux-based model reference adaptive system(RF-MRAS)and non-linearity of the inverter in the output voltage degrade the speed response of the sensorless operation of the electric drive system in terms of DC drift,initial value issues,and inaccurate voltage acquisition.To improve the speed response,a compensating voltage component is supplemented by an amending integrator.The compensating voltage is a coalition of drift and offset voltages,and reduces DC drift and initial value issues.During low-speed operation,inaccurate voltage acquisition distorts the stator voltage critically,and it becomes considerable when the stator voltage of the machine is low.Implementing a three-level neutral point clamped inverter in speed-sensorless decoupled control of an induction motor improves the performance of the drive with superior quality of inverter output voltage.Further,the performance of the induction motor drive is improved by replacing the proportional-integral(PI)controller in the adaption mechanism of RF-MRAS with an adaptive neuro-fuzzy inference system(ANFIS)controller.A prototype model of the three-level neutral point clamped inverter(3L-NPC)-fed induction motor drive is fabricated in a laboratory,and its performance for a RF-MRAS,modified RFMRAS,and modified RFMRAS using ANFIS are compared using different benchmark tests.
基金Supported by National Natural Science Foundation of China under Grant 51477003Beijing Natural Science Foundation under Grant 4152013.
文摘Model reference adaptive system(MRAS)is typically employed for rotor position/speed estimation in sensorless interior permanent magnet motor(IPMSM)drives.The adjustment of control parameters in MRAS is a key issue for IPMSM drive systems with cyclic fluctuating loads.In order to avoid the difficulties involved with manual tuning of the control parameters,a new MRAS scheme based on fuzzy logic is proposed in this paper in which a fuzzy controller replaces the conventional PI regulator.To implement this new MRAS scheme,a two-dimensional(2-D)fuzzy rule is designed.The proposed control scheme is employed in the IPMSM drives with cyclic fluctuating loads such as compressors.In order to lower the motor speed ripple caused by the cyclic fluctuating load,a feed-forward compensation strategy with the load-matching motor output torque pattern is developed.Experimental results demonstrate the feasibility and effectiveness of the proposed fuzzy logic based MRAS scheme with minimal rotor position estimation error.
文摘In this paper a fuzzy logic （FL） based model reference adaptive system （MRAS） speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller （FLC） for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic （PV） energy source is used. To extract the maximum power from the PV source, a constant voltage controller （CVC） is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.
