Real World Implementation of Fuzzy Anti-Swing Control for a Behavior-Based Intelligent Crane System
There exist several industrial applications for large crane systems. Most of
them experience serious problems with load swing. This research presents a fuzzy
based control scheme to minimize load swing for crane systems while maintaining
continuous payload transportation. The control system of the crane is built using
behavior-based approaches. In the control system developed, each module generates
behaviors, and improvement in the performance of the system proceeds by adding new
modules to the system. In order to develop the anti-swing module, a fuzzy logic
controller is applied using information extracted from potentiometers. The fuzzy
controller provides a Mechanism for dealing with imprecise sensor data. The anti-swing
behaviors are successfully implemented by formulating a set of fuzzy rules. The
simulation and experimental results of the system show that the system remains stable
under several operating situations. In this study, the control of a multi-crane system
composed of two industrial overhead
cranes operating in the same workspace is studied.
The goal of this multi-crane system is to control the
two cranes to move the payloads in the same workspace without causing collisions.