The purpose of this study is to design and control position and torque based on the steering controller of power tiller simulator developed by the National Institute of Agricultural Sciences. The tiller simulator selects sensors and motors to detect the motion of the mechanism required for steering, and controls the tiller's steering controller through the PID control method and the PWM control method which can control simultaneously the position and torque. Simulation tests are carried out under various conditions to verify the efficiency of the proposed controller. The power tiller training simulator can be used as a means to prevent agricultural machinery accidents caused by human factors. Through the simulator, the driver can experience a variety of tasks without any risk of collision, the results of his actions, and learn the cause and effect concepts, which can be used for safety education and accident experience.

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㎧.

To improve the productivity in the harbor, successful development of an UCT(Unmanned Container Transporter) is needed. Well-designed steering and velocity control systems are the key factor for the development of the UCT. In this paper, a research concerning the achievement of the steering control is introduced. To get an information on the guide line that the UCT should track, the vision system is applied. By using neural network, proper steering angle is gotten fast with less influence of the image disturbance. A simulation based on the UCT kinematics is performed with the measured steering angle, and it shows satisfactory results.