• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.303-306
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• 1997

Magnetic bearings have been adopted to support the rotor by electromagnetic force without mechanical contact and have many advantages. The application of the magnetic bearings have become more and more widespread in recent years. But magnetic bearings require feedback control for stable operation because they are inherently open loop unstable systems. In this study, H infinity controller has been applied for rotor-magnetic bearing system for vibration control. The result showed that H infinity controller has better performance than PID controller through simulations.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.249-250
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• 2006

In this paper, hardware design and implementation of digital controller for the High Precision Digital Power Supply (HPDPS) based on Digital Signal Processor (DSP) and Field Programmable Gate Array (FPGA) is presented. Developed digital controller is composed of high resolution Digital Pulse Width Modulation (DPWM) and high resolution analog to digital converter circuit with anti-aliasing filter. And Digital Signal Processor (DSP) has the capability of a few micro-second calculation time for one feedback loop. 32-bit DSP and DPWM with 150[ps] step resolution is used to implement the HPDPS. Also 18-bit 2 mega sample per second ADC board is adopted for the developed digital controller. Also, hardware structure of the developed digital controller and experimental results of the first prototype board for HPDPS is described.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.154-161
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• 1999

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.6
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• pp.176-187
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• 1995

The problem of designing intelligent cruise control system for a longitudinal motion of an automobile, which is powered by internal combustion engines coupled to an automatic multispeed transmission, is considered. The basic concept is a vehicle-following system which maintains desired spacing between vehicles. This system actuates throttle with the information of the spacing error so as to maintain proper spacing and improve passenger ride comfort. In designing the controller, a modified controller, i.e, PID gain scheduling and fuzzy controller with fuzzy compensator was developed in order to overcome the nonlinearities of the automobile and obtain better performance. The computer simulation results illustrate that the better vehicle responses were obtained with the modified fuzzy controller and, under this controller, the vehicle responses were found to be relatively insensitive to parameter variations.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.567-574
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• 2006

This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2473-2475
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• 2001

In trajectory tracking methods, the error values of current position and velocity are compensated to follow the given reference path and velocity. The path tracking for a wheeled mobile robot is treated in this paper. It is very difficult to implement stable trajectory tracking algorithms because mobile robots have kinematically non-holonomic constraints. For solving this problem, a velocity controller is presented in this paper. This velocity controller is designed by a PID controller which could be easily employed. In this case, velocity errors caused by system uncertainties or internal and external disturbances could exist. A neural network is used for compensating the velocity errors. Input variables of this neural network compensator are defined by differences between the velocities of the posture controller and the real velocities of the mobile robot. Simulation results show the effectiveness of the proposed controller.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1024-1026
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• 1996

Sources of nonlinearity In a fuzzy logic controller Include the fuzzification, the fuzzy reasoning and the defuzzification. In this paper, a closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two Inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity Is analyzed with respect to the conventional PID control and the sliding mode control.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.243-247
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• 2004

The dynamometers which had made in a long time ago could not control the input/output quantity of water minutely and was sensitive to a noise since it was controlled by an analog control method. Therefore, a fully digital controlled system was urgently required to be robust against various noises. In this paper, the new system which can control the amount of circulated water in dynamometer was developed. This system is consisted of an industrial digital type controller and a servo motor. The industrial PLC was used as a main controller for the developed system, and the actuator and servo motor were used to control the inlet and outlet valve independently. The torque signal of load cell was fed back to the main controller to regulate the diesel engines load. Generally, an input/output valve position of the old dynamometer was fixed with a proper situation for an engine output test and the torque was changed according to the time interval. However, the torque value for the dynamometer could not be constantly kept because of the variation of the input water flow and fluid characteristic. Therefore, the automatic control of an inlet and outlet valve should be performed to keep the constant torque. So, the PID control method was applied to solve this problem. Also, the development of a web-based remote control system was described in this paper. This software will give us the convenience of operation, the more efficient operations, and the reduced operator workload for operation of the dynamometer. The application results of the system have been verified at actual diesel engine field.