• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.7-14
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• 2015

To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a high gain observer-based robust speed controller design for a linear induction motor (LIM) drive. The force disturbance as well as the mechanical parameter variations such as the mass and friction coefficient gives a direct influence on the speed control performance of APS. To guarantee a robust control performance, the system uncertainty caused by the force disturbance and mechanical parameter variations is estimated through a high gain disturbance observer and compensated by a feedforward manner. While a time-varying disturbance due to the mass variation can not be effectively compensated by using the conventional disturbance observer, the proposed scheme shows a robust performance in the presence of such uncertainty. A Simulink library has been developed for the LIM model from the state equation. Through comparative simulations based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.93-101
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• 1993

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.5
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• pp.83-93
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• 1996

In this paper, a minimum variance control system is proposed and practically implemented, which is adequate to the induction motor speed control system with frequent load variation. Minimum variance control method is used as a control law and recursive least square method with selective forgetting factor is proposed and analyzed with general forgetting algorithm as an estimation method. Designed control system is based on PC-DSP structure for the purposed of easiness of applying adaptive algorithm. Through computer simulation and experimental results, it is verified that proposed control system is robust to the load variation and practical implementation is possible.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.2
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• pp.38-46
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• 1998

A theoretical and an empirical application of the speed control of a single-shaft turbo-jet engine was done using an observer for Linear Quadratic Gausian(LQG) that is one of the robust control fields. Based on a general controller design with state feedback, a controller with output feedback was designed to find out a sufficient condition in finding an Asymptotic Stability After defining of the total system through the modeling of a real turbo-jet engine, a Tracking Control was carried out. Furthermore, a saturation of the control input was theoretically considered in the output feedback controller to simulate more similar real condition.

• Journal of Power Electronics
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• v.15 no.3
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• pp.730-740
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• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.136-136
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• 2000

The direct drive servo valve(DDV) is composed of a DC rotor, link, valve spool and displacement sensor(LVDT) where the spool is directly coupled to the DC motor through the link. Since the DDV is a kind of one-stage valve, the robust controller is required to overcome the flow force effect on the spool motion. The mathematical equations are derived and the stability, accuracy and response speed of a DDV are investigated analytically using a linearized system block diagram. Proportional control, PID control. Time-Delay control, Sliding Mode control, and Proportional control using the load pressure are applied to DDV to find which one shows the best control performance. The digital computer simulation results show that the proportional control using the load pressure satisfies the design requirement of response speed and steady state error regardless of the variation of load pressure,

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.4
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• pp.1-7
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• 2002

QFT is a very practical design technique that emphasizes the use of feedback for achieving the desired system performances in despite of plant uncertainties and disturbances. The loop shaping procedure of QFT is employed to design the robust controller, until the desired bounds are satisfied. This paper presents an optimization algorithm for designing PID controller using the loop shaping of QFT. The proposed method identifies the parameter vector of PID controller from a linear system that develops from rearranging the two dimensional system matrices and output vectors obtained from the QFT bounds. The feasibilities of the suggested algorithm are illustrated with a turbine speed control problem.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.67-77
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• 2014

An electric motor is the one of the most important parts in robot systems, which mainly drives the wheel of mobile robots or the joint of manipulators. According to the requirement of motor performance, the controller type and parameters vary. For the wheel driving motors, a speed tracking controller is used, while a position tracking controller is required for the joint driving motors. Moreover, if the mechanical parameters are changed or a different motor is used, we might have to tune again the controller parameters. However, for the beginners who are not familiar about the controller design, it is hard to design pertinently. In this paper, we develop a nominal robust controller model for the velocity tracking of wheel driving motors and the position tracking of joint driving motors based on the disturbance observer (DOB) which can reject disturbances, modeling errors, and dynamic parameter variations, and propose the methodology for the determining the least control parameters. The proposed control system enables the beginners to easily construct a controller for the newly designed robot system. The purpose of this paper is not to develop a new controller theory, but to increase the user-friendliness. Finally, simulation and experimental verification have performed through the actual wheel and joint driving motors.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1868-1870
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• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1679-1680
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• 2008

DC motor has been widely used in industrial applications, because the performance is excellent on the speed and position system. However, when a system has parameter uncertainty, it is very difficult to guarantee its performance. Sliding mode control is robust for parameter uncertainty. However conventional sliding mode control can not have the properties of PID controller because its sliding surface has lower order dynamics than the original system. In this paper the sliding surface design method is proposed by using virtual state for DC motor speed control. Its design is based on the augmented system whose dynamics have one higher order than that of the original system. As a result, in spite of the parameter uncertainty, the proposed sliding surface can have the same dynamic of nominal system controlled by PID controller. And the reaching phase is removed by setting an initial state which makes the initial sliding surface equal to zero.