Real-time implementation of a Kalman filter for sway angle using laser slot senor signals

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Supervisor:
Dr. Kiss Bálint
Department of Control Engineering and Information Technology

Cranes are widely used in industries requiring rapid and precise transport of materials.

These devices contributed to numerous interesting problems in the field of control engineering

due to their highly nonlinear, underactuated nature and practical importance.

The wire ropes holding the load come in many different configurations but their baseline

differential flatness can be utilized for implementing a specific nonlinear control law.

However, for the nonlinear state feedback we need real-time information on the most

significant state variable - which happens to be the underactuated one - the rope angle.

This might prove diffcult in a noisy industrial environment. In contrary to many real-time

methods, laser slot sensors mounted on the moving crane provide robust asynchronous

signals at certain angle values were effective in estimating the angle.

The aim of this study is to examine the efficiency of the sensor fusion algorithm based

on motor encoder and laser slot sensor signals. Using this estimation, the implementation

of a real-time nonlinear control law is documented. The possible extension of this laser slot

sensor-based concept to three-dimensional overhead cranes is also elaborated on within the

frame of a computer simulation.

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