• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.2
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• pp.51-57
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• 2004

Vector control schemes are used in inverter-fed induction motor drives to obtain high performance. Crucial to the success of the vector control scheme is the knowledge of the instantaneous position of the rotor flux. However, the position of the rotor flux change with temperature and magnetic saturation of the motor. This variation cause deterioration of both steady state and dynamic operation of the motor drives. Performance degradation is in the form of input-output torque nonlinearity and saturation of the motor. Analytic expressions are derived to evaluate the effects due to parameter sensitivity. Also, dynamic response is shown by speed command with the variation of stator and rotor resistance.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1352-1354
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• 2005

In this paper, an improved dead time compensation method which is concerned about dead time and extra time in Pulse-Width-Modulation(PWM) period is presented comparing the existing dead time compensation. The voltage drop across the switches are modeled excluding effect of stray capacitor. A low pass filter(LPF) is adopted for accurate detecting of current polarity. The method is based on Space-Vector-Pulse-Width-Modulation(SVPWM). All simulation results are presented using MATLAB and Simulink.

• Journal of Power Electronics
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• v.17 no.4
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• pp.953-962
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• 2017

Momentum flywheels are widely applied for the generation of small and precise torque for the attitude control and inertial stabilization of satellites and space stations. Due to its inherited system nonlinearity, the tracking performance of the flywheel torque/speed in dynamic/plug braking operations is limited when a conventional controller is employed. To take advantage of the well-separated two-time-scale quantities of a flywheel driving system, the singular perturbation technique is adopted to improve the torque tracking performance. In addition, the composite control law, which combines slow- and fast- dynamic portions, is derived for flywheel driving systems. Furthermore, a novel control strategy for plug braking dynamics, which considers couplings between the Buck converter and the three-phase inverter load, is designed with easy implementation. Finally, experimental results are presented to demonstrate the correctness of the analysis and the superiority of the proposed methods.

• Journal of Power Electronics
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• v.4 no.1
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• pp.1-11
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• 2004

A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper. Torque ripple in the DTC system for high power induction motor could be drastically reduced with the foregoing researches of switching voltage selection and torque ripple reduction algorithms. However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. In this paper, the inherent uncertainty is approximated on-line by the RBFN, and an additional robust control term is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented. Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system.

• Transactions on Electrical and Electronic Materials
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• v.15 no.6
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• pp.297-304
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• 2014

Due to the nonlinearity and complexity of the three-phase photovoltaic inverter, we propose an intelligent control based on fuzzy logic and the classical proportional-integral-derivative. The feedback linearization method is applied to cancel the nonlinearities, and transform the dynamic system into a simple and linear subsystem. The system is transformed from abc frame to dq0 synchronous frame, to simplify the state feedback linearization law, and make the close-loop dynamics in the equivalent linear model. The controls improve the dynamic response, efficiency and stability of the three-phase photovoltaic grid system, under variable temperature, solar intensity, and load. The intelligent control of the nonlinear characteristic of the photovoltaic automatically varies the coefficients $K_p$, $K_i$, and $K_d$ under variable temperature and irradiation, and eliminates the oscillation. The simulation results show the advantages of the proposed intelligent control in terms of the correctness, stability, and maintenance of its response, which from many aspects is better than that of the PID controller.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1156-1165
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• 2018

This paper presents a detailed realization of direct torque controlled induction motor drive for elevator applications. The drive is controlled according to the well-known space vector modulated direct control scheme (SVM-DTC). As the elevator drives are usually equipped with speed sensors, flux estimation is carried out using a current model where two stator currents are measured and accurate instantaneous rotor speed measurement is used to overcome the need for measuring stator voltages. Speed profiling for a comfortable elevator ride and other supervisory control activities to provide smooth operation are also explained. The drive performance is examined and controllers' parameters are fine-tuned using MATLAB/SIMULINK. The blocks used for flux and torque estimation and control in the offline simulation are compiled for real-time using dSPACE Microlabox. The performance of the drive has been verified experimentally. The results show good performance under transient and steady state conditions.