• 전기학회논문지
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• 제66권5호
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• pp.792-799
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• 2017

The real time unmanned monitoring system of an equipment's internal parts and condition requires the monitoring device to be able to stop at a set location on the rail. However, due to the slip between the driving surface and the roller, an error occurs between the actual position and the command position. In this paper, a method to compensate the position error due to the roller slip is proposed. A proximity sensor located at both ends of the rail detects the starting point and the maximum position pulse, linearly compensating the error between the angular position of the motor and the mechanically fixed starting and maximum position pulse of the rail in forward and reverse direction. Moreover, unlike the existing servo position controller, the motor adopts the position detection method of Hall sensor in BLDC (Brushless DC) and applies an algorithm for low-speed driving so that a stable position control is possible. The proposed rail guided unmanned monitoring system with driving slip compensator was tested to verify the effectiveness.

• 한국자동차공학회논문집
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• 제8권4호
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.