• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.910-916
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• 2015

A sensorless motor control scheme with conventional back-Electro Motive Force (EMF) sensing based on zero crossing point (ZCP) detection has been widely used in various applications. However, there are several problems with the conventional method for effectively driving sensorless brushless motors. For example, a phase mismatch of 30 degrees occurs between the ZCP and commutation time. Additionally, most of the motor speed/current controls are achieved based on a pulse width modulation (PWM) method, which generates significant noise that distracts the back-EMF sensing. Due to the PWM switching, the ZCP is not deterministic, and thus the efficiency of the motor is reduced because the phase transition points become uncertain. Moreover, the motor driving performance is degraded at a low speed range due to the effect of PWM noise. To solve these problems, an improved back-EMF detection method based on a differential line method is proposed in this paper. In addition, the proposed sensorless BLDC driver addresses the problems by using a variable voltage driver generated from a buck converter. The variable voltage driver does not generate the PWM switching noise. Consequently, the proposed sensorless motor driver improves 1) the signal-to-noise ratio of back-EMF, 2) the operation range of a BLDC motor, and 3) the torque characteristics. The proposed sensorless motor driver is verified through simulations and experiments.

• Proceedings of the KIEE Conference
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• summer
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• pp.1251-1253
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.1
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• pp.48-52
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• 2011

Over the years, traditionally, six-switch three-phase inverters have been widely utilized for variable speed alternating current motor drives. Recently, some efforts have been made on the application of four-switch three phase inverter for uninterruptible power supply and variable speed drives. This is due to some advantages of the four-switch three phase inverter over the conventional six-switch three-phase inverters such as reduced price due to reduction in number of switches, reduced switching losses, reduced number of interface circuits to supply logic signals for the switches, simpler control algorithms to generate logic signals, less chances of destroying the switches due to lesser interaction among switches, and less real-time computational burden. However such as slow di/dt and speed limitation, are the inherent characteristics and main drawbacks of the four-switch configuration. Those problems can be overcome in conjugation with Voltage-doublers which has additional advantage, such as unity power factor correction.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.181-185
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• 2000

To get high efficiency in variable speed control of induction motor it is required that the vector control should be separated from flux components current and torque component current. In this paper the vector control is modeled by the estimation of the stator flex. Representing induction motor speed controller as a digital system with he use of he 32bit DSP improves the motor control performance The IGBT is used as the switching device and the validity of the proposed vector control is proved through voltage current wave and the characteristics of the velocity response as the drive circuit being simplified

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.1044-1046
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• 1993

This paper describes a switching strategy for variable speed control and low torque ripple of Switched Reluctance Motor(SRM). The main advantage of this strategy is simple control. Therefore it can be constructed easily. And a design principle of SRM is represented for the proposed switching strategy. The proposed switching method is tested by simulation and experiment on various SRM type. As a result, The SRM drive with the proposed scheme is effective in reducing the torque ripple and variable speed control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1509-1512
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• 2003

The electric power wheelchair needs to control motor torque and speed for responding to variable actions given by handling a joystick. In this paper a DSP-based BLDC motor controller using a single dc-link current sensor is presented for electric power wheelchair. It is composed by a DSP processor and three-phase inverter module. To control torque, high speed current control is achieved by the PI controller and pulse width modulation (PWM) signals with 25 kHz carrier frequency, which is performed by 200 ${\mu}sec$ cycle. The speed controller computes the new direct current reference from the speed error and the PI control equation. The displacement value by handling the joystick is converted to reference speeds of right and left wheel motors using nonholonomic wheelchair kinematics. Experimental results show that the presented control system is enough to implement a speed servo in wheelchair driving.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.736-741
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• 1998

It is well known that an encoder or a resolver is necessary to obtain the position data for speed or position control Generally utilized speed sensors are mal-affected by the EMI, dusty, and high temperature surroundings. Therefore, the speed and position sensorless controls using observers have been studied widely. In this paper, the binary observer which is composed of two feedback regulation loops to control the speed of SRM(Switched Reluctance Motor) is applied. One loop compensates the control input directly like the sliding mode control, and the other one compensates the system parameters indirectly. This observer is constructed on the foundation of variable structure control on the foundation of variable structure control theory and has the inertial term for the varying parameter. The validities of this proposed method is proved by experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.691-696
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.224-234
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• 2008

Multi-phase machines can be used in variable speed drives. Their applications include electric ship propulsion, 'more-electric aircraft' and traction applications, electric vehicles, and hybrid electric vehicles. Multi-phase machines enable independent control of a few numbers of machines that are connected in series in a particular manner with their supply being fed from a single voltage source inverter(VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases more than or equal to five-phase. The number of series-connected machines is a function of the phase number of VSI. Theoretical and simulation studies have already been reported for number of multi-phase multi-motor drive configurations of series-connection type. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information concerning the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an MRAS estimator based sensorless control of a vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed-voltage, fixed-frequency supply, and hysteresis current control are presented for various operating conditions on the basis of simulation results. The purpose of this paper is to report the first ever simulation results on a sensorless control of a five-phase two-motor series-connected drive system. The operating principle is given followed by a description of the sensorless technique.

• Journal of Power Electronics
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• v.7 no.1
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• pp.81-88
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• 2007

This paper presents a new approach to the automatic control of the turn-off angle used to excite the Switched Reluctance Motor (SRM) employed in electric vehicles (EV). The controller selects the turn-off angle that supports and improves the performance of the motor drive system. This control scheme consisting of classical current control and speed control depends on a lookup table to take the best result of the motor. The turn-on angle of the main switches of the inverter is fixed at $0^{\circ}C$ and the turn-off angle is variable depending on the reference speed. The motor, inverter and control system are modeled in Simulink to demonstrate the operation of the system.