Robust anti – swing control of 3D crane system using GA – FUZZY

This paper proposes an alternative fuzzy logic controller to create the anti-swing controller of the 3D crane system. Simultaneously, it uses more genetic algorithms (GA) to optimize the parameters inside the crane controller. The controller's purpose controls the crane's position and maintains the smallest payload swing angle possible at the desired position in order to reduce industrial accidents and increase work performance. In addition, we create a new fuzzy rule which is more effective than other fuzzy rules or controllers. This completely solves the position control but the payload swing angle is still small, making it difficult for the other controllers. Moreover, the simulated results from the proposed fuzzy rule demonstrate better robust stabilization when compared with the other fuzzy rules or controllers.