• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.349-352
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• 1997

In this paper, we propose a new longitudinal controller of automated vehicles. The controller is designed based on a sliding control method, which is known to be robust to disturbances and modelling errors. Contrary to currently available sliding controller, a switching controller gain method is suggested. It is shown throughout simulations that the proposed controller reduces the amount of overshoot, which may derive smoother velocity tracking in a platoon.

• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.331-352
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• 2022

This study used a latent growth curve models(LGCM) to examine longitudinal changes in youth's game usage, self-control and the longitudinal mediation effect of adaptive game use in the relationship between game usage and self-control. A four-year longitudinal data of 863 adolescents from the Game User Panel Survey, provided through participation in the 2019 Game User Panel Research Conference hosted by the Korea Creative Contents Agency, was used to verify the longitudinal mediation effect of adaptive game use. SPSS 21 was used to verify the normality of variables from each wave, and to conduct correlation analysis. Mplus 6.12 was used to verify the longitudinal mediation effect. The results are as follows. First, game usage, self-control and adaptive game yielded linear temporal growth. Second, latent growth curve models showed that the direct effect of game usage on self-control was insignificant, but game usage had a significant indirect effect on self-control through adaptive game use. Continuous adaptive gaming increased self-control. Third, sobel test results showed that both the initial value and change rate of adaptive game use had a full-mediation effect, confirming the longitudinal mediation effect. This study verified the longitudinal change of self-control affected by change in game usage and adaptive game use.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• 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.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.861-866
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• 2007

This paper presents development of a vehicle lateral and longitudinal control for autonomous driving control and test results obtained using an electric vehicle. Sliding control theory has been used to develop a vehicle speed and distance control algorithm. The longitudinal control algorithm that maintains safety and comfort of the vehicle consists of a cruise and STOP&GO control depending on traffic conditions. Desired steering angle is determined through the lateral position error and the yaw angle error based on preview optimal control. Motor control inputs have been directly derived from the sliding control law. The performance of the autonomous driving control which is integrated with a lateral and longitudinal control is investigated by computer simulations and driving test using an electric vehicle. Electric vehicle system consists of DC driving motor, an electric power steering system, main controller (Autobox)

• Journal of Mechanical Science and Technology
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• v.16 no.9
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• pp.1166-1174
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• 2002

This paper presents the implementation and vehicle tests of a vehicle longitudinal control scheme for Stop and Go cruise control. The control scheme consists of a vehicle-to-vehicle distance control algorithm and throttle/brake control algorithm for acceleration tracking. The desired acceleration of a vehicle for vehicle-to-vehicle distance control has been designed using Linear Quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. A millimeter wave radar sensor has been used for distance measurement. A stepper motor and an electronic vacuum booster have been used for throttle/brake actuators, respectively. It has been shown that the proposed control algorithm can provide satisfactory performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.202-213
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• 1999

Adaptive Cruise Control (ACC) is one of key features on intelligent Transportation System(ITS). In ACC, the steering is done by a driver, but the engine throttle valve and the brake are controlled electronically. The relative velocity and distance from the preceeding vehicle are measured by radars or image processing units and relevant vehicular spacing is maintained in ACC control systems. In this study, vehicle longitudinal dynamics are modeled to simulate vehicle longitudinal maneuver and to design longtitudinal controllers for ACC vehicles. The control algorithm is designed based on the modeled vehicle longitudinal dynamics using a non-linear sliding mode control method. To verity the performance of the control algorithm, a real time numerical simulation program is developed on a Silicon Graphics workstation using C-language . A real time graphic program is alos develpe and integrated with the numerical simulation program.

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.371-389
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• 2019

The implementation of a robust $H_{\infty}$ Control, which is numerically efficient for uncertain nonlinear dynamics, on longitudinal and lateral autopilots is realised for a quarter scale Piper J3-Cub model accepted as an unmanned aerial vehicle (UAV) under the condition of sensor noise and disturbance effects. The stability and control coefficients of the UAV are evaluated through XFLR5 software, which utilises a vortex lattice method at a predefined flight condition. After that, the longitudinal trim point is computed, and the linearization process is performed at this trim point. The "${\mu}$-Synthesis"-based robust $H_{\infty}$ control algorithm for roll, pitch and yaw displacement autopilots are developed for both longitudinal and lateral linearised nonlinear dynamics. Controller performances, closed-loop frequency responses, nominal and perturbed system responses are obtained under the conditions of disturbance and sensor noise. The simulation results indicate that the proposed control scheme achieves robust performance and guarantees stability under exogenous disturbance and measurement noise effects and model uncertainty.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.803-812
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• 2006

In order to reduce the negative effects of dynamic coupling among vehicle subsystems and improve the handling performance of vehicle under severe driving conditions, a vehicle chassis control integration approach based on a main-loop and servo-loop structure is proposed. In the main-loop, in order to achieve satisfactory longitudinal, lateral and yaw response, a sliding mode controller is used to calculate the desired longitudinal, lateral forces and yaw moment of the vehicle; and in the servo-loop, a nonlinear optimizing method is adopted to compute the optimal control inputs, i.e. wheel control torques and active steering angles, and thus distributes the forces and moment to four tire/road contact patches. Simulation results indicate that significant improvement in vehicle handling and stability can be expected from the proposed chassis control integration.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.295-301
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• 2001

In this paper, an impedance control using a serial chain of spring-damper system is proposed for a vehicle platoon. For safety of the vehicle platoon, it is required to regulated the distance between each vehicle at a preassigned value even in case of vehicle model error, or moise in the measurement signal. Since the spring-damper system is physically stable and widely used to represent the interaction with the uncertain environments, it is appropriate to the longitudinal control of the vehicle platoon. By considering the nonholonomic characteristics of the vehicle motion, the lateral control and the longitudinal control of the vehicle paltoon are unified in the proposed algorithm. Computer simulation is carried out to verify the robustness against the uncertainties such as the vehicle model error and the measurement noise.