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This book provides extensive information about advanced control techniques in electric drives. Multiple control and estimation methods are studied for position and speed tracking in different drives. Artificial intelligence tools, such as fuzzy logic and neural networks, are used for specific applications using electric drives.

History of engineering & technology --- PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence --- PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book provides extensive information about advanced control techniques in electric drives. Multiple control and estimation methods are studied for position and speed tracking in different drives. Artificial intelligence tools, such as fuzzy logic and neural networks, are used for specific applications using electric drives.

PMSM drive --- current control --- deadbeat predictive control --- equivalent input disturbance --- BSAII --- Euclidean distance --- energy management --- E-REV --- overhead transmission line --- UAV inspection --- safe distance --- multi-source data fusion --- adaptive threshold --- permanent magnet synchronous motor --- second-order sliding mode control --- cascade control --- robustness --- PMSM --- model predictive control --- parameter identification --- hybrid electric vehicles (HEVs) --- mode transition --- adaptive sliding mode control (A-SMC) --- clutch actuator --- PI observer --- fractional order proportional-integral-differential (FOPID) --- indirect vector control --- position control of motor --- induction motor --- sensorless control --- sliding mode observer --- RBFNN-based self-tuning PID controller --- I-f startup strategy --- PMLSM --- position sensorless control --- high-frequency square-wave voltage injection --- FIR filter --- maglev train --- automotive electric powertrain --- rotor position sensor --- resolver --- inductive position sensor --- eddy current position sensor --- Hall sensor --- magnetoresistive position sensor --- Hall sensors --- brushless direct current motor drive system --- power electronics --- industrial application --- integrated electric drive system --- electromechanical coupling --- harmonic torque reduction strategy --- quantized --- nonlinear systems --- time delay --- lyapunov approach --- real-time implementation --- neural fuzzy controller --- I-f control strategy --- fractional order control --- synergetic control --- sliding mode control --- motor drives --- advanced control --- power converters --- estimation --- sensor --- artificial intelligence