• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.52-60
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• 2005

Generally, a voltage difference or voltage distortion exists between the reference voltage and the practical voltage applied to a motor in a pulse width modulated(PWM) voltage source inverter(VSI). This voltage distortion varies with the operating conditions such as the temperature, DC link voltage, and phase current level. Also the voltage distortion affects the machine current distortion, torque pulsations, and control performance. In this paper, the voltage distortion in a PWM VSI is analyzed and a new on-line estimation method based on the model reference adaptive system(MRAS) is proposed to compensate the time varying voltage distortion, while considering the parameter variations for a permanent magnet synchronous motor (PMSM). The simulation and experimental results show the effectiveness of the proposed voltage difference observer and the compensation method.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1832-1833
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• 2006

This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of Autonomous Underwater Vehicle(AUV) steering systems. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome nonlinearities and uncertainty. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and original signal of AUV model that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by gradient-descent method. Through computer simulations, we demonstrate the effectiveness of the proposed control method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.

• Journal of Power Electronics
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• v.9 no.3
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• pp.343-353
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• 2009

In this paper, a nonlinear controller is proposed for Doubly-Fed Induction Machine (DFIM) drives. The nonlinear controller is designed based on an adaptive backstepping control technique, using a fifth order model of an induction machine in the synchronous d & q axis rotating reference frame, whose d axis coincides with the space voltage vector of the main AC supply, and using the rotor current and stator flux components as state variables. The nonlinear controller can perfectly track the torque reference signal measured in the stator terminals under the condition of unity power factor regulation, in spite of the stator and rotor resistance variations. In order to make the drive system capable of operating in the motoring and generating modes below and above the synchronous speed, two level Space-Vector PWM (SV-PWM) back-to-back voltage source inverters are employed in the rotor circuit. It is confirmed through computer simulation results that the proposed control approach is effective and valid.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.2
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• pp.36-40
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• 1993

In order to improve complicated construction and complex control which are disadvantage of optimal PWM technique aimed at harmonic elimination method, this paper presented MRA(Model Reference Adaptive) PWM technique that gatmg signal of inverter is generated by comparing the reference signal with the induced feedback signal at the reference model of load. Design of controller is composed of microprocessor and analog circuit. MRA PWM technique used in the paper is able to compensate the degradation of voltage efficiency to be generated by the ratio of the output voltage to the DC supply voltage being low for using conventional sinusoidal PWM technique. When the trapezoidal signal is employed as the reference signal. the low order harmonics of line current can be reduced and the switching pattern is made by on-line computation using comparatively simple numerical analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.150-156
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• 2001

This paper proposed a speed estimator using MRAC(Model Reference Adaptive Control) for sensorless vector control. It is robust for parameter variation or disturbance and the estimated speed is used as feedback in a vector control system. Experiment is presented to confirm the theoretical analysis.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.845-851
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• 2008

A simple RMRAC (Robust Model Reference Adaptive Control) scheme for the PMSM (Permanent Magnent Synchronous Motor) is proposed in the synchronous frame. A current control of PMSM is the most inner loop of electro-mechanical driving systems and it requires a fast and simple control law to play a foundation role in the control hierarchy. In the proposed synchronous current model, the input signal is composed of a calculated voltage by proposed adaptive laws and real system disturbance. The gains of feed-forward and feedback controllers are estimated by the proposed modified Gradient method respectively, where the system disturbances are assumed as filtered current tracking errors. After the estimation of the system disturbances from the tracking errors, the corresponding voltage is fed forward to control input voltage to compensate for the disturbances. The proposed method is robust against high frequency disturbance and has a fast dynamic response. It also shows a good real-time performance due to it's simplicity of control structure. Through the simulations and real experiments, efficiency of the proposed method is verified.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.739-744
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• 2000

A robust control algorithm under disturbance and reference change is developed using a self tuning control method incorporting of the well known internal model principle and the annihilator polynomical. The types of disturbance and reference signal are assumed to be given as known difference polynomials. The algorithm is shown for a minimum phase system with parameters of unknown parameters.