• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.41-46
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• 2004

In this paper, we study the stabilization control if an underwater vehicle from its initial posture to its desired one. We assume tint the underwater vehicle has velocity constraint, i.e. it has no velocity component for some direction. Our approach is based on the nonholonomic system which am derived from velocity constraints that cannot integrable. We proposed a control strategy for posture control of the underwater vehicle using multi-rate digital control. The proposed control scheme is applied to the berthing control if an underwater vehicle and verified the effectiveness if control strategy by numerical simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.29-35
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• 2018

This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.206-211
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• 2011

In this paper, a control algorithm for the improvement of yaw and velocity stability of electrical vehicle with two or four in-wheel motors is proposed. The vehicle is modeled with independently operative in-wheel motor wheels. Different frictions on the wheels are regarded as disturbances, which causes driving instability. In this situation the proposed algorithm enables stabilizing the yaw motion and velocity of vehicle simultaneously. The proposed PID controller is composed with two techniques, which enhance the disturbance reject and point tracking performances. One is nonlinear gain function and the other one is improved integral controller operating as time based weight function. Simulation is conducted to reveal its efficient performance.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.3
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• pp.107-117
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• 2019

When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.645-654
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• 2023

Based on first-order shear deformation theory, a wave propagation model of graphene platelets reinforced metal foams (GPLRMFs) circular plates is built in this paper. The expressions of phase-/group- velocities and wave number are obtained by using Laplace integral transformation and Hankel integral transformation. The effects of GPLs pattern, foams distribution, GPLs weight fraction and foam coefficient on the phase and group velocity of GPLRMFs circular plates are discussed in detail. It can be inferred that GPLs distribution have great impacts on the wave propagation problems, and Porosity-I type distribution has the largest phase velocity and group velocity, followed by Porosity-III, and finally Porosity-II; With the increase of the GPLs weight fraction, the phase- and group- velocities for the GPLRMFs circular plate will be increased; With the increase of the foam coefficient, the phase- and group- velocities for the GPLRMFs circular plate will be decreased.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.565-570
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• 2001

Vehicle dynamics control (VDC) system requires more information on driving conditions compared with ABS and/or TCS. In order to develop the VDC system, tire slip angles, vehicle side-slip angle, and vehicle lateral velocity as well as road friction coefficient are needed. Since there are not any cheap and reliable sensors, recent researches on parameter estimation have given rise to a number of parameter estimation techniques. This paper presents new vehicle model to estimate vehicle's yaw rate. This model is improved from the conventional 2 degrees of freedom vehicle model, so-called bicycle model, taking nonlinear effects into account. These nonlinear effects are: (i) tyre nonlinearity; (ii) lateral load transfer during cornering; (iii) variable gear ratio with respect to vehicle velocity. Estimation results are validated with the experimental results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.2
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• pp.107-113
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• 2019

In this paper, a robust filter based wind velocity estimation algorithm without an air velocity sensor in an air vehicle is presented. The wind velocity is useful information for the air vehicle to perform precise guidance and control. In general, the wind velocity can be obtained by subtracting an air velocity which is obtained by an air velocity sensor such as a pitot-tube, and a ground velocity which is obtained by a navigation equipment. However, in order to simplify the configuration of the air vehicle, the wind estimation algorithm is necessary because the wind velocity can not be directly obtained if the air velocity measurement sensor is not used. At this time, the aerodynamic coefficient of the air vehicle changes due to the turbulence, which causes the uncertainty of the system model of the filter, and the wind estimation performance deteriorates. Therefore, in this study, we propose a wind estimation method using $H{\infty}$ filter to ensure robustness against aerodynamic coefficient uncertainty, and we confirmed through simulation that the proposed method improves the performance in the uncertainty of aerodynamic coefficient.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.14-19
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• 2012

On-line and real-time information of the longitudinal velocity is the essential factor for the Advanced Vehicle Control Systems such as ABS(Anti-lock Brake System), TCS(Traction Control System), ESC (Electronic Stability Control) etc. However, the longitudinal velocity cannot be easily measured or calculated during braking maneuvering. A new algorithm is presented for the estimation of the longitudinal velocity with the measurements of the vehicle longitudinal/lateral acceleration, steering angle and yaw rate. The algorithm is designed utilizing the Extended Kalman Filter based on the 3 degree of freedom vehicle model. In order to compensate for the biased sensor signal on the inclined road, the inclined angle is also estimated. The performance of the proposed estimation algorithm is evaluated in field tests.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.137-144
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• 2000

In this paper, a longitudinal control of the lead vehicle for a platoon in IVHS Regulation Layer is proposed. The backstepping method has been used for the controller design. This method has an advantage in that its stability need not be proven since the controller is designed based on the Lyapunov Function. The control object is that the lead vehicle tracks a reference velocity and maintains a safe distance between the inter-platoons while the followers are keeping the speed of the lead vehicle of a platoon. The coordinate of system is transformed to a new coordinate system for its convenience to design controller. The new coordinate system is composed of error and new error variable. The error is the difference between the safe distance and the actual distance of inter-platoons. A new error variable is the difference between the velocity of vehicle and the estimated state of a system operated by the virtual input. The Lyapunov function is obtained based on the variables of new coordinate system. In the computer simulation, several cases have been studied such as when the lead vehicle is tracking the optimal speed. or a lead vehicle of the following platoon tracks the velocity of the previous platoon while maintaining a safe distance. Also a nonlinear engine time constant case has been investigated. All the simulation results show that the designed controller satisfies the control object sufficiently.