• Journal of Welding and Joining
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• 제16권3호
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• pp.55-63
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• 1998

Among the position sensing methods available, the arc sensor which utilizes the electrical signal obtained from the welding arc itself is one of the most prevalently used methods, because it has an advantage that no particular sensing device is necessary and real-time sensing of a groove position is possible directly under the arc. The authors have already developed a seam tracking system that contains a new arc sensor algorithm, which uses the relative welding current variation according to the tip-to-workpiece distance in GMA welding. In this study a torch height control algorithm for automatic weld seam tracking was proposed for completing the previous system, which uses an on-off control technique. To implement the torch height control algorithm during weld seam tracking the system parameters which include 2nd averaging range, weighting factor for 2nd moving averaging, and Z-directional basic compensation distance were determined by experimental analysis. Finally the two different height control methods, one is simple on-off control and the other on-off control using a reference current value , were compared in their tracking abilities.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.93-100
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• 2003

Accuracy in maneuvering target tracking using multiple models relies upon the suit-ability of each target motion model to be used. To construct multiple models, the interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require predefined sub-models and predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers. To solve these problems, this paper proposes the GA-based IMM method as an intelligent tracking method for a maneuvering target. In the proposed method, the acceleration input is regarded as an additive process noise, a sub-model is represented as a fuzzy system to compute the time-varying variance of the overall process noise, and, to optimize the employed fuzzy system, the genetic algorithm (GA) is utilized. The simulation results show that the proposed method has a better tracking performance than the AIMM algorithm.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.241-246
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• 2004

This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1740-1751
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• 2018

This paper proposes a novel fault tolerant tracking control (FTTC) scheme for a class of nonlinear systems with actuator failures based on the policy iteration (PI) algorithm and the adaptive fault observer. The estimated actuator failure from an adaptive fault observer is utilized to construct an improved performance index function that reflects the failure, regulation and control simultaneously. With the help of the proper performance index function, the FTTC problem can be transformed into an optimal control problem. The fault tolerant tracking controller is composed of the desired controller and the approximated optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, and the approximated optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. By establishing a critic neural network, the PI algorithm is utilized to solve the Hamilton-Jacobi-Bellman equation, and then the approximated optimal feedback controller can be derived. Based on Lyapunov technique, the uniform ultimate boundedness of the closed-loop system is proven. The proposed FTTC scheme is applied to reconfigurable manipulators with two degree of freedoms in order to test the effectiveness via numerical simulation.

• IEIE Transactions on Smart Processing and Computing
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• 제5권6호
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• pp.375-382
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• 2016

This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.236-246
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• 2006

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• 한국정밀공학회지
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• 제21권11호
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• pp.83-90
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• 2004

In this paper we present a new real-time visual servoing unit for laparoscopic surgery This unit can automatically control laparoscope manipulator through visual tracking of laparoscopic surgical tool. For the tracking, we present two-stage adaptive CONDENSATION(conditional density propagation) algorithm to extract the accurate position of the surgical tool tip from a surgical image sequence in real-time. This algorithm can be adaptable to abrupt change of laparoscope illumination. For the control, we present virtual damper system to control a laparoscope manipulator safely and stably. This system causes the laparoscope to move under constraint of the virtual dampers which are linked to the four sides of image. The visual servoing unit operates the manipulator in real-time with locating the surgical tool in the center of image. The experimental results show that the proposed visual tracking algorithm is highly robust and the controlled manipulator can present stable view with safe.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1318-1326
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• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.

• 조명전기설비학회논문지
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• 제24권2호
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• pp.33-38
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• 2010

최근 태양광 발전시스템은 정부 에너지 정책에 의해서 널리 보급되고 있다. 여기에 광전지 전력생산의 효율을 높이기 위해서는 견실한 태양 추적식이 필요하다. 하지만 태양추적 식은 추적기술의 미비에 의해서 아직 널리 보급되지 못하고 있다. 이를 해결하기 위해서 본 논문에서는 태양광전지의 최대전력추적을 위해서 태양광센서 및 신경회로망 제어알고리즘을 적용하였다. 태양추적 센서는 평판위에 한 개의 사각기둥과 동, 서, 남, 북 4개의 광센서로 구성된다. 태양추적 2축 제어는 두 개의 모터에 의해서 각각 동작되며, 모터의 제어 입력은 신경회로망 제어 알고리즘에 의해서 계산된다. 제안된 제어방식의 기능은 태양추적광 발전 실험에 의해서 확인하였으며, 본 논문의 태양추적방식은 고정식 보다 32[%]효율을 증가시켰다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.958-959
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• 2015

This paper proposes adaptive incremental conductance(A-IC) algorithm for maximum power point tracking(MPPT) control of photovoltaic. Conventional Perturbation & Observation(PO) and IC MPPT control algorithm generally uses fixed step size. A small fixed step size will cause the tracking speed to decrease and tracking accuracy of the MPP will decrease due to large fixed step size. Therefore, this paper proposes N-IC MPPT algorithm that adjust automatically step size according to operating conditions. To improve tracking speed and accuracy, when operating point is far from maximum power point(MPP), step size uses maximum value and when operating point is near from MPP, step size uses variable step size that adjust according to slope of P-V curve. The validity of MPPT algorithm proposed in this paper prove through compare with conventional IC MPPT algorithm.