• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.117-122
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• 2006

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. 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 induction motor using FLC-FNN and estimation of speed using 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 proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.20-27
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• 1994

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an improved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.315-320
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• 1998

In this paper, we present the PID control method for the controlling flow rate of highly complicated nonlinear Left Ventricular Assist Device(LVAD) with pneumatically driven mock circulatory system. Beat Rate (BR), Systole-Diastole Rate (SDR) and flow rate are used as the main variables of the LVAD system. System modeling is completed using the neural network with input variables (BR, SDR, their derivatives, actual flow) and an output valiable(actual flow). Then, as the basis of this model, we perform the simulation of PID control to predict the performance and tendency of the system and control the flow rate of LVAD system using the PID controller. The ability and effectiveness of identifying and controlling a LVAD system using the proposed algorithm will be demonstrated through computer simulation and experiments.

• Proceedings of the KIEE Conference
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• summer
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• pp.920-922
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• 2004

This paper presents a speed control system for a linear induction motor(LIM) with cage-type secondary using direct thrust control(DTC). The actual speed of the LIM is detected by the linear scale with the resolution of $100{\mu}m$. Thrust correction coefficient due to the end effect of the LIM is utilized in estimating actual thrust. As a result, responses of the thrust, current, speed, and flux are shown.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.36-44
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• 2013

This paper is written for the development and application of boiler fuel control algorithm and distributed control system of coal-fired power plant by the steps of design, coding, simulation test, site installation and site commissioning test. Fuel control algorithm has the upper algorithm and it is boiler master control algorithm that controls the fuel, feed water, air by generation output demand. Generation output demand by power load influences fuel control. Because fuel can not be supplied fast to the furnace of boiler, fuel control algorithm was designed adequately to control the steam temperature and to prevent the explosion of boiler. This control algorithms were coded to the control programs of distributed control systems which were developed domestically for the first time. Simulator for coal-fired power plant was used in the test step. After all of distributed control systems were connected to the simulator, the tests of the actual power plant were performed successfully. The reliability was obtained enough to be installed at the actual power plant and all of distributed control systems had been installed at power plant and all signals were connected mutually. Tests for reliability and safety of plant operation were completed successfully and power plant is being operated commercially. It is expected that the project result will contribute to the safe operation of domestic new and retrofit power plants, the self-reliance of coal-fired power plant control technique and overseas business for power plant.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.410-415
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• 2013

This paper proposes a bidirectional platoon control law using a coupled distance error based on the backstepping-like feedback linearization control method for an interconnected mobile agent system with a string structure. Unlike the previous results where the single agent was controlled using the only own information without other agents, the proposed control law cannot show the only distance error convergence of each agent, but also the string stability of the whole system. Also, the control performances are improved by the proposed control law in spite of low performance of bidirectional control strategy in the previous results. The proposed bidirectional platoon control algorithm is based on the backstepping-like feedback linearization control method. The position errors between each agent and the preceding and the behind agents are coupled by weighted summation. By the proposed control law, the distance error of each agent can converge to zero while the string stability is guaranteed when the coupled errors can converge to zero. To this end, the back-stepping control method is employed. The pseudo velocity input is determined considering the kinematic relationship between agents and the string stability. Then, the actual dynamic control input is determined to make the actual velocity converge to the pseudo velocity input. The stability analysis and the simulation results of the proposed method are included in order to demonstrate the practical application of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.3
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• pp.117-126
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• 2013

This paper is written for the development and application of boiler furnace pressure control algorithm and distributed control system of coal-fired power plant by the steps of design, coding, simulation test, site installation and site commissioning test. The control algorithms were designed in the shape of cascade control for two parts of furnace pressure control and induced draft fan pitch blade by standard function blocks. This control algorithms were coded to the control programs of distributed control systems. The simulator for coal-fired power plant was used in the test step and automatic control, sequence control and emergency stop tests were performed successfully like the tests of the actual power plant. The reliability was obtained enough to be installed at the actual power plant and all of distributed control systems had been installed at power plant and all signals were connected mutually. Tests for reliability and safety of plant operation were completed successfully and power plant is being operated commercially. It is expected that the project result will contribute to the safe operation of domestic new and retrofit power plants, the self-reliance of coal-fired power plant control technique and overseas business for power plant.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.57-64
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• 2006

This paper is proposed for a artificial neural network(ANN) sensorless control based on the vector controlled induction motor drive, or proposes a adaptive fuzzy teaming control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed for a method of the estimation of speed of induction motor using 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 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 analysis results to verify the effectiveness of the new method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.6
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• pp.503-511
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• 2004

In this study, for estimating responses of a controlled structure and determining the maximum control force of velocity-dependent damping devices, three estimation models such as Fourier envelope convex model, probability model, and Newmark design spectrum are used. For this purpose, a procedure is proposed for estimating actual velocity using pseudo-velocity and this procedure considers the effects of damping ratio increased by the damping device. Time history results indicate that actual velocity should be used for estimating accurate maximum control force of damping device and Newmark design spectrum modified by the proposed equation gives the best estimation results for over all period structures.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.24-33
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• 1996

PLCs are vital components of modern automation systems, which have penetrated into almost every industry. Many industries have a demand for facilitation of PLC programming. In this study, a programning system for sequential control is developed on a personal computer. This programming system consists of two main parts, a GRAFCET editor and a GRAFCET compiler. The GRAFCET editor enables us to model an actual sequential process by a GRAFCET diagram. This GRAFCET editor is developed by the menu-driven method based on specific menus and graphic symbols. The GRAFCET compiler consists of two parts, a GRAFCET parser and a code generator. The possible errors in a drawn GRAFCET diagram are first checked by the GRAFCET parser which generates finally an intermediate code from a verified CRAFCET diagram. Then the intermediate code is converted into a control code of an actual sequential controller by the code generator. To show the usefulness of this programming system, this system is applied to a pneumatically controlled handling robot. For this robot, a Z-80 microprocessor is used as the actual sequential controller.