Load Swing Suppression in Jib Crane Systems Using a Genetic Algorithm-trained Neuro-controller

A neuro-controller for load swing suppression in a jib crane system involving only rotation about the vertical axis is proposed. The controller is trained by a genetic algorithm, substantially simplifying the design of the controller. As such a system is nonholonomic, the conventional control problem is difficult to solve, requiring knowledge of complex control theory. Using a simple three-layered neural network as a controller genetic algorithm-based training, it is demonstrated that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.