Genetic Algorithm Optimized PI and Fuzzy Sliding Mode
Speed Control for DTC Drives
Abstract— This paper presents a detailed comparison between
a conventional PI controller and a variable structure controller
based on a fuzzy sliding mode strategy used for speed control
in direct torque control induction motor drive. Genetic algorithms
are used to tune the PI controller gains to ensure optimal
performance. The performance of the two controllers are
investigated and compared for different dynamic operating
conditions such as of reference speed and for load torque step
changes at nominal parameters and in the presence of parameter
variation and imprecision. Results show that the PI controller has
better performance for nominal operating conditions while the
fuzzy sliding mode is more robust against parameter variation
and uncertainty, and is less sensitive to external load torque
disturbances with a fast dynamic response.
more pdf
DIRECT TORQUE CONTROL OF INDUCTION MOTOR
WITH FUZZY MINIMIZATION TORQUE RIPPLE
Direct torque control (DTC) is receiving wide atten-
tion in the recent literature [1, 2]. DTC minimizes the use
of machine parameters [3, 4]. This type of control is es-
sentially a sliding mode stator flux-oriented control. The
DTC uses the hysteresis band to directly control the flux
and torque of the machine. When the stator flux falls out-
side the hysteresis band, the inverter switching stator is
changed so that the flux takes an optimal path toward
the desired value [3, 4].
The name direct torque control is derived from the
fact that on the basis of the errors between the reference
and the estimated values of torque and flux it is possible
to directly control the inverter states in order to reduce
the torque and flux errors within the prefixed band limits
[5, 6].
Speed Control for DTC Drives
Abstract— This paper presents a detailed comparison between
a conventional PI controller and a variable structure controller
based on a fuzzy sliding mode strategy used for speed control
in direct torque control induction motor drive. Genetic algorithms
are used to tune the PI controller gains to ensure optimal
performance. The performance of the two controllers are
investigated and compared for different dynamic operating
conditions such as of reference speed and for load torque step
changes at nominal parameters and in the presence of parameter
variation and imprecision. Results show that the PI controller has
better performance for nominal operating conditions while the
fuzzy sliding mode is more robust against parameter variation
and uncertainty, and is less sensitive to external load torque
disturbances with a fast dynamic response.
more pdfDIRECT TORQUE CONTROL OF INDUCTION MOTOR
WITH FUZZY MINIMIZATION TORQUE RIPPLE
Direct torque control (DTC) is receiving wide atten-
tion in the recent literature [1, 2]. DTC minimizes the use
of machine parameters [3, 4]. This type of control is es-
sentially a sliding mode stator flux-oriented control. The
DTC uses the hysteresis band to directly control the flux
and torque of the machine. When the stator flux falls out-
side the hysteresis band, the inverter switching stator is
changed so that the flux takes an optimal path toward
the desired value [3, 4].
The name direct torque control is derived from the
fact that on the basis of the errors between the reference
and the estimated values of torque and flux it is possible
to directly control the inverter states in order to reduce
the torque and flux errors within the prefixed band limits
[5, 6].
more pdf
IMPROVED DTC OF INDUCTION MOTOR WITH FUZZY
IMPROVED DTC OF INDUCTION MOTOR WITH FUZZY
RESISTANCE ESTIMATOR
Abstract- The aim of the work is to study the
feasibility of stator resistance estimator in DTC
scheme. Fuzzy logic is used to estimate the stator
resistance. DTC with fuzzy estimator is characterized
by fast torque and flux response in very-low speed
operation.
Abstract- The aim of the work is to study the
feasibility of stator resistance estimator in DTC
scheme. Fuzzy logic is used to estimate the stator
resistance. DTC with fuzzy estimator is characterized
by fast torque and flux response in very-low speed
operation.
more pdf
DIRECT TORQUE NEURO FUZZY SPEED CONTROL
OF AN INDUCTION MACHINE DRIVE BASED
ON A NEW VARIABLE GAIN PI CONTROLLER
This paper presents an original variable gain PI (VGPI)
controller for speed control of a simplified direct torque neuro
fuzzy controlled (DTNFC) induction motor drive. First, a
simplified direct torque neuro fuzzy control (DTNFC) for a voltage
source PWM inverter fed induction motor drive is presented.
This control scheme uses the stator flux amplitude and the
electromagnetic torque errors through a four rules adaptive NF
inference system (ANFIS) to generate a voltage space vector
(reference voltage). This voltage is used by a space vector
modulator to generate the inverter switching states. Then a VGPI
controller is designed in order to be used as the speed controller
in the simplified DTNFC induction motor drive. Simulation
of the simplified DTNFC induction motor drive using VGPI for
speed control shows promising results. The motor reaches
the reference speed rapidly and without overshoot, load
disturbances are rapidly rejected and the detuning problem
caused by the stator resistance variation is fairly well dealt with.
DIRECT TORQUE NEURO FUZZY SPEED CONTROL
OF AN INDUCTION MACHINE DRIVE BASED
ON A NEW VARIABLE GAIN PI CONTROLLER
This paper presents an original variable gain PI (VGPI)
controller for speed control of a simplified direct torque neuro
fuzzy controlled (DTNFC) induction motor drive. First, a
simplified direct torque neuro fuzzy control (DTNFC) for a voltage
source PWM inverter fed induction motor drive is presented.
This control scheme uses the stator flux amplitude and the
electromagnetic torque errors through a four rules adaptive NF
inference system (ANFIS) to generate a voltage space vector
(reference voltage). This voltage is used by a space vector
modulator to generate the inverter switching states. Then a VGPI
controller is designed in order to be used as the speed controller
in the simplified DTNFC induction motor drive. Simulation
of the simplified DTNFC induction motor drive using VGPI for
speed control shows promising results. The motor reaches
the reference speed rapidly and without overshoot, load
disturbances are rapidly rejected and the detuning problem
caused by the stator resistance variation is fairly well dealt with.
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