• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.870-875
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• 2008

The main objective of this paper is to control a trajectory tracking of the fish-mimetic robot by CPG (Central Pattern Generator), which is biological approach. CPG is biological neural networks that generate rhythmic movements for locomotion of animals, such as walking, running, swimming and flying. Animals show marvelous ability of autonomous dynamic adaptation for an unsteady fluid dynamic environment or various environments. So, we propose the 3-DOF CPG controller to track the trajectory of the fish robot in plane motion. The conformity of the proposed control algorithm is validated by simulation for a fish robot model, which is made by a commercial dynamic package.

• 동력기계공학회지
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• 제7권3호
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• pp.40-47
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• 2003

In this study, position and force simultaneous trajectory tracking control apparatus with pneumatic cylinder driving system is proposed. The pneumatic cylinder driving system that consists of two pneumatic cylinders constrained in series and two proportional flow control valves offers a considerable advantage as to non-interaction of the actuators because of the low stiffness of the pneumatic actuators. The controller applied to the driving system is composed of a non-interaction controller to compensate for interaction of two cylinders and a disturbance observer to reduce the effect of model discrepancy of the driving system in the low frequency range that cannot be suppressed by the non-interaction controller. The experimental results with the proposed control apparatus show that the interacting effects of two cylinders are eliminated remarkably and the proposed control apparatus tracks the given position and force trajectory accurately.

• 로봇학회논문지
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• 제13권4호
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• pp.256-264
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• 2018

Unlike normal wheels, the Mecanum wheel enables omni-directional movement regardless of the orientation of a mobile robot. In this paper, a robust trajectory tracking control method is developed based on the dynamic model of the Mecanum wheel mobile robot in order that the mobile robot can move along the given path in the environment with disturbance. The method is designed using the impedance control to make the mobile robot to track the path, and the integral sliding mode control for robustness to disturbance. The good performance of the proposed method is verified using the MATLAB /Simulink simulation and also through the experiment on an actual Mecanum wheel mobile robot. In both the simulation and the experimentation, we make the mobile robot move along a reference trajectory while maintaining the robot's orientation at a constant angle to see the characteristics of the Mecanum wheel.

• 한국항공우주학회지
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• 제37권1호
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• pp.42-54
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• 2009

비행체의 최적궤적문제에서는 최적화의 수렴성 및 효율성을 위해 3자유도 운동역학모델이 이용되며, 비선형 추종제어를 위해서는 6자유도 비선형 운동모델이 이용된다. 따라서, 3자유도 운동역학모델을 통해 획득한 최적궤적을 비선형 추종제어의 기준궤적으로 사용하는 경우에 두 모델간의 상이성으로 인한 문제가 발생하게 되며 성능이 보장하지 못한다. 본 논문에서는 이러한 두 모델간의 차이를 완화시키기 위한 새로운 최적궤적 생성 방법을 제안하였으며, 성층권비행선의 실제 구속조건과 성능조건 및 제트 스트림을 고려하여 최적궤적을 생성하고 기존 결과와 비교함으로써 제안한 방법의 장점을 검증하였다.

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.582-590
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• 2007

천정주행 크레인의 고속 권상작업 및 흔들림 억제 궤적추종을 위한 비선형 적응제어 방법을 제시한다. 천정주행 크레인의 흔들림 운동은 트롤리의 가속도. 권상로프의 길이 및 권상속도와 강하게 결합되어 있다. 이는 비간섭 제어 기반의 흔들림 억제 궤적추종 제어법칙을 설계하는데 있어 장애요인으로 작용한다. 이러한 문제를 해결하기 위해, 트롤리의 가속도와 권상속도의 영향을 최소화하는 방법으로 불확실성이 존재하는 경우에도 흔들림 운동의 궁극적 균일 유계성을 보장하는 퍼지 비선형 적응형 흔들림 억제 궤적추종제어법칙을 제안한다. 특히, 제안한 방법은 파라미터 변화. 외란 등을 포함한 시스템 불확실성을 퍼지 불확실성 관측기를 이용하여 보상한다. 따라서, 퍼지관측기의 근사화 오차가 영으로 수렴할 때 추종오차 및 흔들림 각도의 궁극적 한계치는 영으로 감소한다. 끝으로 제안한 방법의 성능검증을 위한 모의실험 견과를 제시한다.

• 한국항행학회논문지
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• 제25권3호
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• pp.217-222
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• 2021

EOTS(electro-optical tracking system)는 유도무기의 성능 평가를 위해 유도무기를 추적하여 영상을 획득하는데 활용되고 있다. 유도무기에 대한 추적을 잃어버렸을 경우 유도무기가 매우 빠르게 비행하기 때문에 운용자가 이를 다시 포착하는 것은 거의 불가능하다. 레이더나 텔레메트리 데이터를 활용하여 재 포착 하는 방법이 활용되고 있으나 데이터를 실시간으로 수신할 수 있는 통신망의 설치가 수반되어야하기 때문에 장소에 대한 제약이 따른다. 하지만 유도무기 비행시험 수행 시 계산되는 예상 궤적은 실시간으로 수신할 필요 없이 저장해두었다가 사용할 수 있기 때문에 통신망 설비와 관계없이 활용이 가능하다. 본 논문에서는 미리 알고 있는 비행체의 예상 궤적을 활용하여 비행체를 잃어버렸을 시 비행체의 위치를 예상하는 방법을 제안한다. DTW (dynamic time warping)를 통해 예상궤적과 추적궤적을 비교하여 비행체의 각속도를 추정하고 이를 Kalman Filter의 보정단계에서 관측 값으로 활용하여 비행체의 다음 상태를 예측한다. 제안한 방법의 타당성을 실제 비행체 궤적에 적용하여 검증하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1303-1309
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• 2014

In this paper, we present an iterative learning control (ILC) framework for tracking problems with predefined data points that are desired points at certain time instants. To design ILC systems for such problems, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Unlike traditional ILC approaches, an algorithm will be developed in which the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. In another word, it is a direct approach for the multiple points tracking ILC control problem where we do not need to divide the tracking problem into two steps separately as trajectory planning and ILC controller.The strength of the proposed formulation is the methodology to obtain a control signal through learning law only considering the given data points and dynamic system, instead of following the direction of tracking a prior identified trajectory. The key advantage of the proposed approach is to significantly reduce the computational cost. Finally, simulation results will be introduced to confirm the effectiveness of proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.8-11
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• 1996

In impedance control for contact force tracking it is well known that the reference trajectory of the robot is calculated from known environment stiffness. The accuracy of estimating the environment stiffness determines the performance of the resulting force tracking. Here we present a simple technique, called the trajectory modification technique(TMT), of determining the reference trajectory under the condition that the environment stiffness is unknown. Computer simulation studies have shown that force tracking using the proposed technique is excellent for unknown environment with time varying stiffness.

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

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.435-441
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• 2003

This paper addresses that an approximation and tracking control of realtime recurrent neural networks(RTRN) using two-dimensional iterative teaming algorithm for an electro-hydraulic servo system. Two dimensional learning rule is driven in the discrete system which consists of nonlinear output fuction and linear input. In order to control the trajectory of position, two RTRN with the same network architecture were used. Simulation results show that two RTRN using 2-D learning algorithm are able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two identical RTRN was very effective to trajectory tracking of the electro-hydraulic servo system.