• Journal of Engineering Education Research
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• v.15 no.4
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• pp.48-52
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• 2012

The purpose of this paper is to design and implement the user motion pattern control system for the simulated vehicle. After analyzing the user motion patterns in the system, the patterns are used to control the moving direction of the simulated vehicle such as forward, backward, turn right, turn left etc. The patterns in the system around are sent to the simulated vehicle in real time. In order to execute the suggested user motion pattern control system, the Kinect is used for executing the system. The Kinect recognizes the specified user motion patterns and it transmits the data to the user motion pattern control system. There are nine kinds of the user motion patterns in the system for controlling the simulated vehicle. In addition to this, some sensors are used to detect the condition of the simulated vehicle. GPS is also used to estimate the current location of the simulated vehicle and to obtain the driving information.

• Wind and Structures
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• v.15 no.3
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• pp.263-283
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• 2012

This paper presents a framework of nonlinear dynamic analysis of a low-speed moving maglev (magnetically levitated) vehicle subjected to cross winds and controlled using a clipped-LQR actuator with time delay compensation. A four degrees-of-freedom (4-DOFs) maglev-vehicle equipped with an onboard PID (Proportional-Integral-Derivative) controller traveling over guideway girders was developed to regulate the electric current and control voltage. With this maglev-vehicle/guideway model, dynamic interaction analysis of a low-speed maglev vehicle with guideway girders was conducted using an iterative approach. Considering the time-delay issue of unsynchronized tuning forces in control process, a clipped-LQR actuator with time-delay compensation is developed to improve control effectiveness of lateral vibration of the running maglev vehicle in cross winds. Numerical simulations demonstrate that although the lateral response of the maglev vehicle moving in cross winds would be amplified significantly, the present clipped-LQR controller exhibits its control performance in suppressing the lateral vibration of the vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.680-683
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• 1996

The dynamics of the vehicle system has highly nonlinear components such as an engine, a torque converter and variable road condition. This thesis proposes a Fuzzy Logic Algorithm that shows better control performance than Antiwindup PI in the highly nonlinear vehicle system. Traction Control System(TCS), which adjusts throttle valve opening by Fuzzy Logic Algorithm improves vehicle drivability, steerability and stability when vehicle is starting and cornering. When a throttle valve is opened at large degree, Fuzzy Logic Algorithm shows better performances like a small settling time and a small oscillation than Antiwindup PI in simulation. The decreased desired slip ratio improves steerability in the simulation when a vehicle is cornering. The Fuzzy Logic Algorithm has been tested by a 1/5-scale vehicle for tracking the constant desired velocity.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.741-746
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• 2001

This paper presents an investigation of a vehicle-to-vehicle distance control using a Hardware-in-the-Loop Simulation(HiLS) system. Since vehicle tests are costly and time consuming, how to establish a efficient and low cost development tool is an important issue. The HiLS system consists of a stepper motor, an electronic vacuum booster, a controller unit and two computers which are used to form real time simulation and to save vehicle parameters and signals of actuator through a CAN(Controller Area Network). Adoption of a CAN for communication is a trend in the automotive industry. Since this environment is the same as that of a real vehicle, a distance control logic verified in laboratory can be easily transfered to a test vehicle.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.214-230
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• 2014

This paper presents a high performance sensor less control four motorized wheels for electric vehicle. Firstly, we applied a sensor less master-slave DTC based control to both the two in wheel motors by using sliding mode observer for its quick response and its high reliability in electric vehicle application. Secondly, to overcome the possible loss of adherence of one of the four wheels which is likely to destabilize the vehicle a solution is proposed in this paper. Thirdly, a Fuzzy logic anti-skid control structure well adapted to the non-linear system is used to overcome the main problem of power train system in the wheel road adhesion characteristic. Various Simulation results have been include in this paper to show that the proposed control strategy can prevent vehicle sliding and show good vehicle stability on a curved path.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.19-25
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• 2005

This paper presents a lateral control system for the autonomous navigation vehicle that was developed and tested by Robotics Centre of Ecole des Mines do Paris in France. A robust lane detection algorithm was developed for detecting different types of lane marker in the images taken by a CCD camera mounted on the vehicle. $^{RT}Maps$ that is a software framework far developing vision and data fusion applications, especially in a car was used for implementing lane detection and lateral control. The lateral control has been tested on the urban road in Paris and the demonstration has been shown to the public during IEEE Intelligent Vehicle Symposium 2002. Over 100 people experienced the automatic lateral control. The demo vehicle could run at a speed of 130km1h in the straight road and 50km/h in high curvature road stably.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.89-94
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• 2004

In this paper, a safe control strategy is considered in the situation when a platoon of vehicles need to decelerate rapidly. When the vehicles ate spaced closely, it is known that the reference information should be transmitted to the whole platoon to minimize the undesirable effects of small leader disturbances. However, the vehicle control should also depend on the preceding vehicle position to maintain the desired distance. Tracking the preceding vehicle position can lead to amplification of the control input along the following vehicles, therefore the vehicles in the rearward generally exert larger maximum control input than the vehicles in the front. The theoretical bounds for the $i^{th}$ vehicle control input are calculated using a linear vehicle and controller model. In the simple illustrative example, the designed controller maintains string stability, and the control inputs of the following vehicles stay within bounds.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.249-256
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• 2000

This paper deals with the control of the lateral motion of a mobile vehicle. A mobile vehicle using in this experiment is able to adapt many unmanned automatic driving system, for example, like a automated product transporting system. This vehicle is consist of the two servomotors. One is used to accelerate this vehicle and the another is used to change this lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral motion of the vehicle. Therefore, the main aim of this paper is investigate the possibility of applying adaptive fuzzy control algorithms to a microprocessor-based servomotor controller which requires faster and more accurate response compared with many other industrial processes. Fuzzy control rules are derived by modelling an expert's driving actions. Experiments are performed using a mobile vehicle with sensing units, a microprocessor and a host computer.