• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.54-62
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• 1995

This paper is a study on a speed control of an induction motor used the MRA-DSM(Mode1 Reference Adaptive-Discrete Sliding Mode) controller. In this paper, when controls motor speed, DSM algorithm is proposed for having Robustness against disturbance and parameter variation. and it is also proposed MRA-DSM including the additional load model reference algorithm, which can be compensated the discontinuous control imputs at sliding mode and followed the model Preference independent of parameter variation of control subjects. The control system is composed of the parallel processing control system using the microprocessor for maximizing the performance of control systems and the real time processing. Also it simplifies the hardware composed of controlling the system by software and improves the reliability of the system. And while MRA-DSM control, faster response characteristics of 27.2 % is obtained than DSM control.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.616-621
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• 2004

This paper investigated the speed sensorless indirect vector control of a two-phase induction motor to implement adjustable-speed drive for low-power applications. The sliding mode observer estimates rotor speed. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller was analyzed. To define the control action which maintains the motion on the sliding manifold, an 'equivalent control' concept was used. It was simulated and implemented on a sensorless indirect vector drive for 150W two-phase induction motor. The simulation and experimental results demonstrated effectiveness of the estimation method.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.325-327
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• 2005

In this paper, we propose the design of active queue management (AQM) control system using the self-recurrent wavelet neural network (SRWNN). By regulating the queue length close to reference value, AQM can control the congestions in TCP network. The SRWNN is designed to perform as a feedback controller for TCP dynamics. The parameters of network are tunes to minimize the difference between the queue length of TCP dynamic model and the output of SRWNN using gradient-descent method. We evaluate the performances of the proposed AQM approach through computer simulations.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.301-306
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• 2021

In this paper, we propose a modified back-stepping control method in view of the dynamic model of mobile manipulator has the nonholonomic constraints, these constraints should be considered to design a tracking controller for the mobile manipulator. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot systems. and the modified adaptive back0stepping method is applied to constructing the controller. The proposed controller can realize the tracking trajectory of the reference path. The efficiency and robustness of this control method is demonstrated by the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.427-431
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• 1996

The MRAS proposed by Schauder [8] is modified to improve robustness to the change of load torque and/or the variation of the stator resistance. The difference between the voltage and the current model is fed into the current model via proportional and integral gains. In order to generalize the MRAS, supposing that the rotor speed is time varying, we add a compensating term to the current model. It does not alter the Popov's integral inequality condition. Also, the asymptotic stability of the modified MRAS (MMRAS) is shown with the stability proof technique as in the original paper. By the simulation works, it is verified that the MMRAS obtains improved performance than the original MRAS.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.350-357
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• 2005

This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, the proposed sensorless system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because it is difficult to identify rotor resistance simultaneously while estimating rotor speed, a low-accuracy image processor is used to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.574-577
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• 1996

In order to reduce the torque pulsation caused by non-sinusoidal flux distribution of the brushless direct drive motor(BLDDM), a new torque control technique is proposed. The linkage flux of the BLDDM is first estimated by using the model reference adaptive system (MRAS) technique and the instantaneous torque of the BLDDM is then estimated from the mathematical model including this estimated linkage flux. By using the estimated instantaneous torque of the BLDDM, the minor torque control loop to suppress the undesirable torque pulsation is designed. To show the effectiveness of the proposed control scheme, the simulations and experiments are carried out for the DSP-based BLDDM drive system with a power rate of 120W. It is well demonstrated from these results that the torque and speed control performance of the BLDDM is much improved by employing the proposed control scheme.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. 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. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.140-143
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• 1991

This paper describes a compensation method for the rotor resistance variation of induction machines in speed sensor-less vector control system using MRAS(model reference adaptive system). In case of rotor resistance variation, the analysis of the conventional speed sensor-less vector control system using MRAS is presented and the compensation method for rotor resistance variation using Fuzzy logic is proposed. In order to confirm the performance of the proposed algorithm, computer simulation is performed.