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T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.
The purpose of the current study is to predict the hardness distribution in steel products after hot stamping using a quench factor analysis(QFA) coupled with FE-simulations. QFA is a method to predict properties such as hardness and tensile strength based on time-temperature-property(TTP) curves and can determine properties based on the temperature histories. The constants(K1~K5) of QFA were determined using hardness data obtained after various cooling rates. In the current study, a rear side member was selected for evaluation and FE-simulations were performed to obtain the temperature histories during hot stamping. The predicted temperature data were imported into the QFA to calculate the hardness distribution of the hot stamped parts. A hot stamping experiment of the rear side member was conducted to verify the predicted hardness. The simulation results show good agreement with the experimental measurements.