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UAV for Forest Fire Management
Multi-Rotor Rotorcraft
Intelligent Transportation Systems
Multi-Agent Systems
Object Oriented Programming
Virtual Reality Modelling
Autonomous Mobile Robot
Industrial Overhead Cranes
Parking System Using FPGA
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Perception Models for Robots
Multiple UAVs and UGVs
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Nuclear Inspection
Domestic Water Heater
Autonomous Underwater Vehicle
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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.

Please see the demo video here.

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