• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.301-309
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• 2003

The non linear control algorithm with actuator saturation for a randomly excited oscillator has been widely explored and has shown promising results, but the probabilistic analysis of the algorithm has been rarely made due to its non-linear nature and the fact that the analytical solution of probability density function (PDF) for controlled responses does not exist. In this paper, a method for the probabilistic analysis on the non linear control algorithm with actuator saturation is proposed based on the equivalent non linear system method. Numerical examples are given to verify the approximation solution of PDF comparing to a statistically obtained PDF using a Gaussian white noise and a Kanai - Tagimi filtered Gaussian white noise.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.128-136
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• 1995

The problem addressed in this paper is that of the on-line computational burden of time-optimal control laws for quick, strongly nonlinear systems like revolute robots. It will be demonstrated that a large amount of off-line computation can be substituted for most of the on-line burden in cases of time optimization with constrained inputs if differential point-to- point specifications can be relaxed to cell-to-cell transitions. These cells result from a coarse discretization of likely swaths of state space into a set of nonuniform, contiguous volumes of relatively simple shapes. The cell boundaries approximate stream surfaces of the phase fluid and surfaces of equal transit times. Once the cells have been designed, the bang- bang schedules for the inputs are determined for all likely starting cells and terminating cells. The scheduling process is completed by treating all cells into which the trajectories might unex- pectedly stray as additional starting cells. Then an efficient-to-compute control law can be based on the resulting table of optimal strategies.

• Journal of Navigation and Port Research
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• v.42 no.3
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• pp.237-244
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• 2018

When underwater rubble leveling work is carried out by a robot, real-time information on the topography around the robot is required for remote control. If the topographical information with respect to the current position of the robot is displayed as a 3D graphic image, it allows the operator to plan the working schedules and to avoid accidents like rollovers. Up until now, the topographical recognition was conducted by multi-beam sonars, which were only used to assess the quality before and after the work and could not be used to provide real-time information for remote control. This research measures the force delivered to the bucket which presses the mound to determine whether contact is made or not, and the contact position is calculated by reading the cylinder length. A variable bang-bang control algorithm is applied to control the heavy robot arms for the positioning of the bucket. The proposed method allows operators to easily recognize the terrain and intuitively plan the working schedules by showing relatively 3-D gratifications with respect to the robot body. In addition, the operating patterns of a skilled operator are programmed for raking, pushing, moving, and measuring so that they are automatically applied to the underwater rubble leveling work of the robot.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.34-42
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• 2004

In this paper, a double gimbal is used for roll/yaw attitude control of spacecraft and two feedback controllers are designed. One is a PD controller of no phase difference between roll and yaw control input. The other is a PD controller with a phase lag compensator about the yaw control input. The phase lag compensator is designed a first order system and a lag parameter is designed for the control of yaw angle. There are two case simulations for each of controllers; constant disturbance torques and initial errors of nutation. We obtain the results through simulations that a steady-state error and a rising time of yaw angle are developed by the compensator. In this paper, simulation parameters use the values of KOREASAT 1.

• Journal of Advanced Marine Engineering and Technology
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• v.15 no.1
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• pp.85-95
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• 1991

All physical systems are nonlinear to some degree. The examples are relay, backlash, deadzone, saturation element and so on. In the linear control system design, it is useful method to restrict the nonlinearity to the linearity of system over the operation range. It is worth noting that nonlinearities may be intentionally introduced in to a system. A simple of an intentional non-linearity is the Bang-Bang controller which uses the On-Off relay. In this paper, an angular position servosystem made of a DC servomotor controlled by a microcomputer is discribed. Authors use two methods in the design of controller. The one is linear controller designed by the optimal feedback control theory only and the other is nonlinear controller designed by On-Off relay with optimal feedback control theory. To do the real time control, the controller is designed by using 16bit personal computer and A/D.D/A converter(12bit) is used in order to convert the signal. According to this way, the results from real time control are as follows. 2) Under the On-Off controller with hysterisis the influence of disturbance is considerably smaller than the linerar controller. 3) An increase in the sampling period has a destabilizing effect. 4)In the controller performance, the response time of the On-Off controller is longer than that of the linear controller. To close, we note that the On-Off controller with hysterisis is more attractive than the linear controller in the presence of the input limit.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.25.2-25.2
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• 2010

MIRIS는 과학기술위성 3호의 주 탑제체로 우주 및 지구의 적외선 관측을 위한 두 개의 카메라 시스템을 가지고 있으며 이를 위한 적외선 검출용 이미지 센서가 각각 장착되어 있다. 이미지 센서를 통해 검출된 이미지 데이터를 읽기 위해 고속의 데이터 처리가 요구되어 FPGA 구성방식으로 전용 제어기를 구성하였다. 우주 및 지구의 적외선 관측용 이미지 센서는 구성 및 동작방법이 달라 요구기능을 만족하는 각각의 전용 이미지 센서 제어기를 개발했다. FPGA를 이용한 이미지 센서 제어기에는 검출된 이미지를 읽기위한 센서 제어 신호발생기, 아날로그 이미지 신호를 디지털 정보로 변환하는 ADC 제어용 신호 발생기, ADC의 출력 신호를 고속의 직렬 통신선로로 출력 하는 기능 외에 동작 모드 및 동작 상태 입력용 DSP 인터페이스, 고속의 직렬 통신 선로에 MIRIS 상태정보 삽입 기능, 제어기의 기능을 원격지에서 확인 할 수 있는 이미지 패턴 생성기능 등을 가지고 있다. 특히, 이미지를 읽기 위한 동작 시에만 클록 주파수를 인가하는 방법으로 FPGA 내부 회로를 구성하여 전류의 소모량을 최소화 하였다.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.397-400
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• 1989

This study is to design a method of parameter estimation for a second order linear time invarient system of self-tuning controller utilizing the neural network theory proposed by Hopfield. The result is compared with the other methods which are commonly used in controller theories.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.76-79
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• 2002

본 논문에서는 고성능 AC 서보 모터에 대하여 제어 시스템을 구현하고, 제어기를 설계한다. 하드 웨어구성은 모터 전용 저전압 DSP칩인 TMS320LF2407 칩을 이용한다. TMS320LF2407는 최근의 저전력 구동 추세에 따라 3.3V를 구동 전압으로 이용하는 DSP 칩이다 연산 처리 속도는 40MIPS로 빠른 연산 처리능력을 가지고 있지만 주변 소자들과의 인터페이스(보통 5V로 동작)와 노이즈에 대한 대책을 고려하여야 한다. 본 논문에서는 이러한 전압 호환과 노이즈를 가능한 제거한 서보 모터 제어기를 구성하며, 또한 유효 전압 인가시간의 관점에서 바라본 개선된 공간 벡터 PWM방식을 적용함으로써 계산과정과 프로그램을 간단히 하고, 전류제어를 소프트웨어 방식으로 처리하여 복잡한 하드웨어를 간략화 시키고자 한다 이런 과정에 의하여 앞으로 요구될 수 있는 고성능 다기능을 위한 효용성을 높이고자 한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1380-1384
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• 2015

The DC motor has the strong characteristics in the speed response, the system parameter variations and the external influence and is used as the speed controller with its good starting torque in the distributing industry. However development of the Microprocessor which is for high speed switching program can make better control system. This paper introduce to design of the high-effective DC motor controller that is using Software Bang-Bang Program of Fuzzy algorithm and to verify a PI controller and a Fuzzy controller.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1031-1033
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• 1996

Now is an automation age. Therefore it is required that machine can do work which was done by men. Artificial Neural Network was developed by the necessity of this purpose. This paper shows a Predictive Control with a Neural Network. The Neural Network learns an Inverted Pendulum in various situations. Then, it has a power to predict the next state after accept the current state. And the Neural Network directs the Bang-Bang Controller to give input to a plant. It seems like that a human expert looks the state of a plant and then controls the plant. It is used a Feedforward Neural Network and shown control state according to the learning. We could get a satisfactory results after complete learning.