Based on the inertia theorem, this method does not need a complex dynamic model for a crane system, but rather uses trolley position and swing angle data to design the proposed fuzzy projection controller.
This study considers a practical overhead crane control problem of designing a fuzzy control to ensure that the trolley arrives precisely at its destination; the load swing angle approaches to zero, and the energy of input and states is minimized.
The results show that the generation of complex 3D-structured surfaces is affected by many factors which include point spacing, track spacing, swing speed, swing angle, head speed, tool pressure, tool radius, feed rate, polishing depth, polishing cloth, polishing strategies, polishing slurry, etc.
In order to optimize some kinematic and dynamic modeling parameters of the robot, such as the drag coefficient of robot, the angular velocity and swing angle of each joint, a solid model of the 3D-printed robot was built by SolidWorks.
The leg mechanism employs an inverse differential gear drive system providing large leg lift and swing sweep angle about a common pivotal point while being driven collectively by a pair of motors.
The mean value of maximum swing angles of the monitoring line and the swing angle ratio were calculated through the image processing of the experimental videos.
Perfect positioning and suppression of swing angle are achieved in shorter time when both control inputs are applied.
Effects of swing angle (30, 45, and 60°) and air velocity (0.5, 1, 1.5 m/s) were investigated.
The system reads everything about your swing — angle of attack, ball and club speed, path to the ball and several other calculations I never did understand.
A robust control strategy is developed to achieve the high positioning accuracy, short transportation time and suppression of swing angle for an uncertain over-head crane system.
