• International Journal of Automotive Technology
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• v.6 no.6
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• pp.599-604
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• 2005

A functional suspension model is proposed as a kinematic describing function of the suspension, that represents the relative wheel displacement in polynomial form in terms of the vertical displacement of the wheel center and steering rack displacement. The relative velocity and acceleration of the wheel is represented in terms of first and second derivatives of the kinematic describing function. The system equations of motion for the full vehicle dynamic model are systematically derived by using velocity transformation method of multi-body dynamics. The comparison of test and simulation results demonstrates the validity of the proposed functional suspension modeling method. The model is computationally very efficient to achieve real-time simulation on TMS 320C6711 150 MHz DSP board of HILS (hardware-in-the-loop simulation) system for ECU (electronic control unit) evaluation of semi-active suspension.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.91-96
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• 2001

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate to effectiveness of the proposed techniques.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.142-155
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• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.77-88
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• 2015

The dynamics of relative motion in a perturbed orbital environment are exploited based on Gauss' and Cowell's variational equations. The inertial coordinate frame and relative coordinate frame (Hill frame) are used, and a linear high fidelity model is developed to describe the relative motion. This model takes into account the primary gravitational and atmospheric drag perturbations. Then, this model is used in the design of a navigation, guidance, and control system of a chaser vehicle to approach towards and to depart from a target vehicle in proximity operations. Relative navigation uses an extended Kalman filter based on this relative model to estimate the relative position/velocity of the chaser vehicle with respect to the target vehicle. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system. The corresponding measurement models, process noise matrix, and other filter parameters are provided. Numerical simulations are performed to assess the precision of this model with respect to the full nonlinear model. The analyses include the navigation errors and trajectory dispersions.

• Journal of Drive and Control
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• v.17 no.1
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.160.3-160
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• 2001

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A new control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in ...

• Journal of Mechanical Science and Technology
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• v.14 no.8
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• pp.836-844
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• 2000

In this research any abnormal motion of a vehicle is detected by utilizing the difference between the reference and actual yaw velocities as sell as the information on vehicle slip angle and slip angular velocity. This information is then used as a criterion for execution of the yaw moment control. A yaw moment control algorithm based on the brake control is proposed for improving the directional stability of the vehicle. The controller executes brake controls to provide each wheel with adequate brake pressures, which generate the needed yaw moment. It is shown that the proposed yaw moment control logic can provide excellent cornering capabilities even on low friction roads. This active control scheme can prevent a vehicle from behaving abnormally, and can assist normal drivers in coping with dangerous situations as well as experienced drivers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.8 s.227
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• pp.1125-1134
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• 2004

This paper presents a mathematical model which is about the dynamics of not only a two wheel steering vehicle but a four wheel steering vehicle. A sliding mode ABS control strategy and PID rear wheel control logic are developed to improve the brake and cornering performances, and enhance the stability during emergency maneuvers. The performances of the controllers are evaluated under the various driving road conditions and driving situations. The numerical study shows that the proposed full car model is sufficient to accurately predict the vehicle response. The proposed ABS controller reduces the stopping distance and increases the vehicle stability. The results also prove that the ABS controller can be employed to a four wheel steering vehicle and improves its performance. The four wheel steering vehicle with PID rear wheel controller shows increase of stability when a vehicle speed is high and sharp cornering maneuver when a vehicle speed is low compared to that of a two wheel steer vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.218-218
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• 2000

Advanced Vehicle Control Systems(AVCS) is one of the key elements in Intelligent Transportation Systems(ITS). This paper considers the problem of longitudinal control in vehicle platoon on a straight lane of a highway. In a very simplified situation, longitudinal vehicle dynamics contains many nonlinear elements. The nonlinear characteristics are mainly composed of an engine, a torque converter, and a drag force. In this paper, sliding control, one of nonlinear control methods, is applied to longitudinal automated vehicle control for platooning. Output feedback linearization is also simulated for comparison with the sliding control. Simulations for comparative study for the adopted controllers such as sliding control and output feedback linearization are peformed under the same conditions. This Paper aims at clarifying the characteristics of sliding control and output feedback linearization.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.299-306
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• 2008

The electromagnet in Maglev vehicles controls the voltage in its winding to maintain the air gap, a clearance between the electromagnet and guideway, within an allowable deviation, with strongly interacting with the flexible guideway. Thus, the vibration characteristics of guideway plays important role in dynamics of Maglev vehicles using electromagnet as an active suspension system. The effects of the guideway's vibrational characteristics on dynamics of the Maglev vehicle UTM-01 are analyzed. The coupled equations of motion of the vehicle/guideway with 3 DOFs are derived. Eigenvalues are calculated and frequency response analysis is also performed for a clear understanding of the dynamic characteristics due to guideway vibration characteristics. To verify the results, tests of the urban Mgalev vehicle UTM-02 are carried out. It is recommended that the natural frequency of the guideway be minimized and its damping ratio in the Maglev vehicle with a 5-states feedback control law as a levitation control law.