• 한국항공우주학회지
• /
• 제34권8호
• /
• pp.71-78
• /
• 2006

본 논문에서는 직교 좌표계에서 추적필터가 설계될 때, 표적의 거리와 방위에 대한 관측오차 공분산의 변화를 고려하기 위하여 정상상태 칼만필터의 해석적 해를 이용하는 IMM 추적기를 설계하였다. 제안된 정상상태 칼만필터 기반 IMM 추적기의 성능분석 및 검증을 위하여 거리의 변화가 작은 표적과 거리의 변화가 큰 표적에 대하여 각각 100회의 Monte Carlo 시뮬레이션을 수행하고, 고정이득 및 칼만필터 기반의 IMM 추적기와 RMS 오차분석을 통하여 비교하였다. 모의실험 결과로부터 제안된 방법이 칼만필터 기반 IMM 추적필터에 비하여 연산량을 크게 감소시킬 수 있으며, 유사한 추적성능을 제공할 수 있음을 확인하였다.

• 한국태양에너지학회 논문집
• /
• 제29권2호
• /
• pp.39-46
• /
• 2009

Heliostat, as a mirror system tracking the sun's movement, is the most important subsystem determining the efficiency of solar thermal power plant. Thus the accurate sun tracking performance under the various hazardous operating condition, is required. This study presents a methodology of development of the solar ray tracing technique and the application of it in the analysis of sun tracking error due to the heliostat geometrical errors. The geometrical errors considered here are the azimuth axis tilting error and the elevation axis tilting error. We first analyze the geometry of solar ray reflected from the heliostat. Then the point on the receiver, where the solar ray reflected from the heliostat is landed, is computed and compared with the original intended point, which represents the sun tracking error. The result obtained shows that the effect of geometrical error on the sun tracking performance is varying with time(season) and the heliostat location. It also shows that the heliostat located near the solar tower has larger sun tracking error than that of the heliostat located farther.

• 정보처리학회논문지A
• /
• 제10A권1호
• /
• pp.35-42
• /
• 2003

본 논문은 이동 에이전트를 추적하는 기존 메커니즘들을 심층 분석하여 문제점을 도출하였고, 이러한 문제점을 해결한 분산 이벤트 서비스 기반 에이전트 추적 모델을 제안하였으며, 이를 적용한 에이전트 감시 시스템을 구현하여 제안한 추적 모델의 성능을 분석하였다. 안한 에이전트 추적 모델은 에이전트 이동이 발생하여도 에이전트 추적이 항상 가능하며, 다중 클라이언트가 동시에 한 에이전트를 추적할 수도 있게 한다. 그리고 에이전트가 이동할 때마다 이를 추적하는 모든 클라이언트에게 위치를 알려주어 클라이언트가 항상 정확하게 에이전트 위치를 파악할 수 있게 하는 위치추적 유형과 메시지를 전달하는 통로를 항상 신뢰할 수 있는 상태로 설정하는 경로설정 유형을 모두 지원한다.

• 제어로봇시스템학회논문지
• /
• 제16권8호
• /
• pp.766-770
• /
• 2010

In this paper, we present an effective covariance tracking algorithm based on adaptive size changing of tracking window. Recent researches have advocated the use of a covariance matrix of object image features for tracking objects instead of the conventional histogram object models used in popular algorithms. But, according to the general covariance tracking algorithm, it can not deal with the scale changes of the moving objects. The scale of the moving object often changes in various tracking environment and the tracking window(or object kernel) has to be adapted accordingly. In addition, the covariance matrix of moving objects should be adaptively updated considering of the tracking window size. We provide a solution to this problem by segmenting the moving object from the background pixels of the tracking window. Therefore, we can improve the tracking performance of the covariance tracking method. Our several simulations prove the effectiveness of the proposed method.

• 제어로봇시스템학회논문지
• /
• 제18권5호
• /
• pp.502-508
• /
• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• 제어로봇시스템학회논문지
• /
• 제22권9호
• /
• pp.693-698
• /
• 2016

A decentralized control method is proposed to enable a group of robots to achieve maximum performance in multisensory target tracking while avoiding collision with the target. The decentralized control was designed based on navigation function formalism. The study showed that the multiple agent system converged to the positions providing the maximum performance by the decentralized controller, based on Lyapunov and Hessian theory. An exemplary simulation was given for a multiple agent system tracking a stationary target.

• 한국공작기계학회논문집
• /
• 제13권3호
• /
• pp.126-132
• /
• 2004

This paper proposed trajectory tracking control based on genetic algorithm. Trajectory tracking control scheme are real coding genetic algorithm(RCGA) and back-propagation algorithm(BPA). Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studies 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 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 verity numerical simulations and the results show better performance than constant gain controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.89-92
• /
• 1996

In this paper, we developed visual tracking algorithm using double active bar. The active bar model to represent the object can reduce the search space of energy surface and better performance than those of snake model. However, the contour will not find global equilibrium when driving force caused by image may be weak. To overcome this problem. Double active bar is proposed for finding the global minimum point without any dependence on initialization. To achieve the goal, an deformable model with two initial contours in attempted to search for a global minimum within two specific initial contours. This approach improve the performance of finding the contour of target. To evaluate the performance, some experiments are executed. We can achieved the good result for tracking a object on noisy image.

• 제어로봇시스템학회논문지
• /
• 제17권8호
• /
• pp.783-789
• /
• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2003년도 춘계학술대회
• /
• pp.893-898
• /
• 2003

Coulomb friction is an important factor for precise position tracking control systems. The control systems with friction causes the steady state error because of being sensitive to the change of system condition and highly nonlinear characteristics. To overcome these problems, we use an estimation scheme of Coulomb friction to experiment for it's compensating. The estimated factor for Coulomb friction is used as a feed-forward compensator to improve the tracking performance of ball-screw systems. The tracking performance was improved by compensating the estimated friction torque in the feed-forward term. And, the sliding mode control which is derived from the Lyapunov stability theorem is applied for robust stability and reducing chattering. The experimental results show that the sliding mode controller with adaptive friction compensator has a good tracking performance compared with the friction uncompensated controller.