• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.179-179
• /
• 2000

An adaptive neural network compensator for stick-slip friction phenomena in servo systems is proposed to supplement the traditionally available position and velocity control loops for precise motion control. The neural network compensator plays a role of canceling the effect of nonlinear slipping friction force. This enables the mechatronic systems more precise control and realistic design in the digital computer. It was confirmed that the control accuracy is more improved near zero velocity and the points of changing the moving direction through numerical simulation

• Smart Structures and Systems
• /
• 제25권5호
• /
• pp.569-580
• /
• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• 제어로봇시스템학회논문지
• /
• 제11권11호
• /
• pp.930-935
• /
• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1008-1013
• /
• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Velocity is controlled by using an optimal state controller LQR. A position control loop is added to form a PD controller. To minimize a position tracking error, neural network is introduced. The reference compensation technique as a neural network control structure is used, and a position tracking error of an autonomous helicopter is compensated by neural network installed in the remotely located ground station. Considering time delays between an autonomous helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network compensation performs better than that of the LQR itself.

• 드라이브 ㆍ 컨트롤
• /
• 제10권1호
• /
• pp.1-6
• /
• 2013

The paper describes a technique that compensates a friction in pneumatic cylinder to perform the position control. The friction is one of the most common nonlinearities present in pneumatic actuating systems. For accurate position control and low velocity control, control strategies usually rely on accurate estimation of friction. This paper presents a observer to estimate the friction force in the pneumatic cylinder from the pressures in cylinder chambers. Also, the stiction compensation of a pneumatic cylinder is obtained by adding pulses to the control signal using impulsive control. The characteristics of the pulses in impulsive control are determined from the control action. The simulation results are proved that the method proposed here is effective.

• 제어로봇시스템학회논문지
• /
• 제10권4호
• /
• pp.341-349
• /
• 2004

In this paper, the decentralized neural network control of the reference compensation technique is proposed to control a 2-DOF inverted pendulum on an x-y plane. The cart with the 2-DOF inverted pendulum moves on the x-y plane and the 2-DOF inverted pendulum rotates freely on the x-y axis. Since the 2-DOF inverted pendulum is divided into two 1-DOF inverted pendulums, the decentralized neural network control is applied not only to balance the angle of pendulum, but also to control the position tracking of the cart. Especially, a circular trajectory tracking is tested for position tracking control of the cart while maintaining the angle of the pendulum. Experimental results show that position control of the inverted pendulum system is successful.

• 대한기계학회논문집A
• /
• 제21권2호
• /
• pp.252-260
• /
• 1997

In this paper, a friction compensation method using a disturbance observer is proposed for an impedance control of pneumatic manipulator. It is assumed that the generated torque by a pneumatic actuator can be estimated based on the pressure signals and the discharge volume. In order to improve the dynamic characteristics of the pneumatic actuator driven by meter out method, we construct the inner torque control system by feeding back the generated torque. In order to reduce the influence of disturbances comprising friction torque and parameter variations of plant, the impedance control system is constructed with a disturbance observer which estimates the disturbances based on the generated torque of pneumatic actuator, the angular velocity and the reaction torque. From some experiments, it is confirmed that the proposed control system is effective to improve the robustness for the friction torque in the impedance control of a pneumatic manipulator.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.91-91
• /
• 2000

In this paper, the error compensation method of the attitude reference system with low-cost IMU is proposed. In general, the attitude error calculated by gyro grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound by accelerometer mixing algorithm and the heading angle can be aided by GPS velocity information. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by medium-grade IMU, LP-81.

• 대한의용생체공학회:의공학회지
• /
• 제19권1호
• /
• pp.9-18
• /
• 1998

본 논문은 초음파 의용 영상에서 인체내의 매질의 초음파 속도의 불균일에 의한 focusing의 저하에 대하여 논하였다. simulation환경으로, 인체 내의 매질 중 속도 값이 가장 큰 차이가 나는 지방(fat)을 일정한 두께로 모델링하였다. 그리고 초음파 빔의 굴절에 의한 진행경로의 변화와 속도차이에 따른 시간지연에 의한 해상도 저하를 구하였다. 그리고 이를 보상하는 방법으로, 보상에 계산량이 많이 필요한 굴절을 무시하고, 속도차에 의한 시간지연만 보상하는 방법을 제안하였다. 제안한 방법을 적용할 경우 현재의 실시간 디지털 focusing 시스템에서 쉽게 구현 가능하다.

• 한국항공우주학회지
• /
• 제46권8호
• /
• pp.662-670
• /
• 2018

고도보정 노즐은 모든 고도에서 최적의 성능을 발휘할 수 있도록 고안된 노즐이다. 발사체의 비추력을 향상시키기 위한 방법으로는 연소실만의 특성인 특성배기속도를 향상시키는 방법과 노즐만의 특성인 추력계수를 향상시키는 방법이 있다. 고도보정 노즐은 동일한 연소기에서 노즐의 성능 개선을 통해 발사체의 성능향상을 가능하게 한다. 고도보정 노즐에 대한 연구는 독일 DLR에서 활발하게 진행되고 있으며, 미국, 러시아, 영국, 호주, 일본 등 항공우주선진국에서도 진행되고 있다. 본 논문에서는 고도보정 노즐에 대한 기술 현황 및 특허 동향에 대해 조사하였다. 이를 바탕으로 고도보정 노즐의 기술흐름을 파악하고 발사체 성능향상 연구에 기초자료로 활용하고자 한다.