• Coupled systems mechanics
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• v.7 no.6
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• pp.707-729
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• 2018

The semi-active optimal vibration control of nonlinear torsion-bar suspension vehicle systems under random road excitations is an important research subject, and the boundedness of MR dampers and the uncertainty of vehicle systems are necessary to consider. In this paper, the differential equations of motion of the coupling torsion-bar suspension vehicle system with MR damper under random road excitation are derived and then transformed into strongly nonlinear stochastic coupling vibration equations. The dynamical programming equation is derived based on the stochastic dynamical programming principle firstly for the nonlinear stochastic system. The semi-active bounded parametric optimal control law is determined by the programming equation and MR damper dynamics. Then for the uncertain nonlinear stochastic system, the minimax dynamical programming equation is derived based on the minimax stochastic dynamical programming principle. The worst-case disturbances and corresponding semi-active bounded parametric optimal control are obtained from the programming equation under the bounded disturbance constraints and MR damper dynamics. The control strategy for the nonlinear stochastic vibration of the uncertain torsion-bar suspension vehicle system is developed. The good effectiveness of the proposed control is illustrated with numerical results. The control performances for the vehicle system with different bounds of MR damper under different vehicle speeds and random road excitations are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.1-91
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• 2001

The subject of this paper is vision system analysis of the autonomous vehicle. But, autonomous vehicle is one of the difficult topics from the point of view of several constrains on mobility, speed of vehicle and lack of environment information. Therefore, we are application of the vision system so that autonomous vehicle. Vision system of autonomous vehicle is likely to eyes of human. This paper can be divided into 2 parts. First, acceleration system and brake control system for longitudinal motion control. Second vision system of real time lane detection is for lateral motion control. This part deals lane detection method and image processing method. Finally, this paper focus on the integration of tole-operating vehicle and autonomous ...

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1248-1256
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• 2001

In this study, a test bed for vehicle longitudinal control is developed using a chassis dynamometer and real time 3-D graphics. The proposed test bed system consists of a chassis dynamometer on which test vehicle can run longitudinally, a video system that shows virtual driver view, and computers that control the test vehicle and realize the real time 3-D graphics. The purpose of the proposed system is to test vehicle longitudinal control and warning algorithms such as Adaptive Cruise Control(ACC), stop and go systems, and collision warning systems. For acceleration and deceleration situations which only need throttle movements, a vehicle longitudinal spacing control algorithm has been tested on the test bed. The spacing control algorithm has been designed based on sliding mode control and road grade estimation scheme which utilizes the vehicle engine torque map and gear shift information.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1253-1263
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• 2002

The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.10
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• pp.104-110
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• 2005

In this paper, unmanned vehicle system and VFF algorithm development with vehicle dynamics is the main topic as a part of Intelligent Transportation System. Unmanned vehicle system is classified by vehicle system and control system. Authors used RC servo motor for longitudinal control via throttle angle, shift lever control, and brake control. For lateral control, authors used step motor, equipped with reduction gear. Unmanned vehicle has nine ultrasonic sensors in front of the unmanned vehicle. After the microcontroller computes the distance between unmanned vehicle and obstacle, the control computer calculates the steering angle enough to avoid the obstacle.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.487-490
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• 2003

In this research, we will devise an obstacle avoidance algorithm for a previously unmanned vehicle. Whole systems consist mainly of the vehicle system and the control system. The two systems are separated; this system can communicate with the vehicle system and the control system through wireless RF (Radio Frequency) modules. These modules use wireless communication. And the vehicle system is operated on PIC Micro Controller. Obstacle avoidance method for unmanned vehicle is based on the Virtual Force Field (VFF) method. An obstacle exerts repulsive forces and the lane center point applies an attractive force to the unmanned vehicle. A resultant force vector, comprising of the sum of a target directed attractive force and repulsive forces from an obstacle, is calculated for a given unmanned vehicle position. With resultant force acting on the unmanned vehicle, the vehicle's new driving direction is calculated, the vehicle makes steering adjustments, and this algorithm is repeated.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.139-145
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• 2004

This paper presents human-in-the-loop evaluations of vehicle stability control(VSC) system using a driving simulator. A driving simulator which contains full vehicle nonlinear model is evaluated by using actual vehicle test data on the same driving conditions. Braking control inputs for Vehicle Stability Control system have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. Closed-loop simulation results at realistic driving situations have shown that the proposed controller reduces driving effort of a driver and enhances stability of a vehicle.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2690-2692
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• 2005

CAN communication can minimize the interfacing lines between equipments because it is composed of only the input and output lines, also is used for automatic system including vehicle, aircraft, railway vehicles and robot because the reliability of data is high by the capability of data-related error detect and correcting function. It can also improve the low-reliable and inefficient system which is composed of the existing Wiring Harness(W/H), so in case of vehicle, it is used in place of the present ECU as the new electro-control unit. In this paper, we constructed the electro-control unit of vehicle by using CAN communication and implemented system that could monitor the condition of vehicle through the web or mobile by connecting the electro-control unit to imbedded system. Such a system is expected to be helpful to the intelligent vehicle and the adoption of ACC(Adaptive Cruise Control).

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.167-172
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• 2006

A design of controller for vehicle dynamic control(VDC) and its implementation on the real vehicle were introduced. The controller has been designed using a three-degrees-of-freedom(3DOF) yaw plane vehicle, and the control algorithm was implemented on the vehicle by control prototyping system dSPACE. A hybrid control algorithm, which makes full use of the advantages of robust and fuzzy control, was adopted in the control system. Field test results show that the performance of the vehicle handling dynamics with hybrid controller is improved obviously compared to that without VDC and with simple robust controller on skiddy roads(friction coefficients lower than 0.3).

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.414-421
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• 2007

This paper presents a engine/brake integrated VDC(Vehicle Dynamic Control) system using neural network algorithm methods for wheel slip and yaw rate control. For stable performance of vehicle, not only is the lateral motion control(wheel slip control) important but the yaw motion control of the vehicle is crucial. The proposed NNPI(Neural Network Proportional-Integral) controller operates at throttle angle to improve the performance of wheel slip. Also, the suggested NNPID controller performs at brake system to improve steering performance. The proposed controller consists of multi-hidden layer neural network structure and PID control strategy for self-learning of gain scheduling. Computer Simulation have been performed to verify the proposed neural network based control scheme of 17 dof vehicle dynamic model which is implemented in MATLAB Simulink.