• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1993-1997
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• 2009

Robust control for DC servo motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, PID-neural network hybrid control method for motor control system is presented. The output of neural network controller is determined by error and rate of error change occurring in load disturbance. The robust control of DC servo motor using neural network controller is demonstrated by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.627-630
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• 2004

The PID type controller has been widely used in industrial application due to its simply control structure, ease of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1223-1232
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• 2004

We present a new technique to the design and real-time implementation of fuzzy control system basedon digital signal processors in order to improve the precision and robustness for system of industrial robot in this paper. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a Fuzzy Logic Controller, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult Self-Organizing Fuzzy Controller is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed Self-Organizing Fuzzy Controller scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.1022-1032
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• 2000

We propose a sliding mode controller tracking the states of a time-varying reference model. The reference model generates the desired trajectories of the states, and the sliding mode controller regulates robustly the errors between the desired states and the measured states. We apply this controller to the overhead crane. Its reference model generates the trajectories of the damped-out swing angle and the swing angular velocity to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. Also, this model generates the desired trajectories of the position and velocity of the crane. The crane model is identified from the experimental data using an orthogonal function. Kalman filtering is applied to estimate the crane states. The designed controller is simulated on a computer and is tested through a 2-ton industrial overhead crane using the vector-controlled servo motor system. It is verified that, from the simulated and experimental results, the sliding mode controller tracking a time-varying reference model works well.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1506-1510
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• 2004

A mobile robot system is developed to inspect the condition of industrial facilities under hot environment. The mobile robot is equipped with internal and external heat insulating material, an internal cooling mechanism, two CCD cameras, wireless communication devices for both the control and image signals, and an embedded controller. The portable controller is equipped with two joysticks for both the mobile robot and the inspection CCD camera, an LCD monitor, and several buttons. The developed mobile robot travels on the internal floor in hot furnaces by operators' joystick operation, captures the images of facilities in the furnaces using a zoom CCD camera, and sends the images to the portable controller through wireless communication. The mobile robot can be operated without any problem under hot environment less than 400$^{\circ}C$ in 30 minutes. This kind of automatic inspection mobile robot can be helpful to prevent significant troubles of industrial facilities without danger of human beings under harmful environment.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.153-156
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• 2007

This paper presents the design, development and performance of a power conditioning system (PCS) for application to a 250kW Molten Carbonate Fuel Cell (MCFC) generation system. A DSP controller was used to control the dc-dc and dc-ac converter operation for grid connection and power injection to the grid. The controller must also supervise the total PCS operation while communicating with the fuel cell system controller. A control method for parallel operation of dc-dc converters was proposed and verified. A 250kW prototype was successfully built and tested. Experimental performances are compared to minimum target requirements of the PCS for MCFC.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.530-532
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• 2007

This paper presents the design, development and performance of a power conditioning system (PCS) for application to a 250kW Molten Carbonate Fuel Cell (MCFC) generation system. A DSP controller was used to control the dc-dc and dc-ac converter operation for grid connection and power injection to the grid. The controller must also supervise the total PCS operation while communicating with the fuel cell system controller. A control method for parallel operation of dc-dc converters was proposed and verified. A 250kW prototype was successfully built and tested. Experimental performances are compared to minimum target requirements of the PCS for MCFC.

• Journal of the Korean Institute of Navigation
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• v.24 no.3
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• pp.147-155
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• 2000

In this paper, we propose the Chaos Fuzzy controller to analyze the chaotic character of time series obtained from the specific plant and to predict the short-term for power consumption of the plant using the Fuzzy controller. We compared the predicted data with the active ones and checked the error generated by them after we time series of supplied power to the proposed controller. As a result of the simulation, we obtained a admirable consequence that the proposed controller can be advanced through various and accurate data acquisition, and continuous analysis of the resident and industrial environment.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2161-2163
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• 2002

The PID type controller has been widely used in industrial application doc to its simply control structure, ease of design and inexpensive cost. However control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (Fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuazy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controlled is better than that of the conventional controller.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.4
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• pp.59-65
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• 1985

This paper presents a design of the PWM digital servo controller and a real-time trajectory planning algorithm and a trajectory tracking algorithm for industrial robot. To be specific, a decentralized control system with hierarchical structure for industrial robot, related hardware and software, and monitor program for convinence of user are implemented. Actually, it was recognized by experiments that continuous path control on the R4 plane was possible using the above servo controller and control algorithms.