Vibration control of load for rotary crane system using neural network with GA-based training

A neuro-controller for vibration control of load in a rotary crane system involving rotation about the vertical axis only is proposed. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a non continuous feedback controller. We propose a simple three-layered neural network as a controller genetic algorithm-based training in order to control load swing suppression for the rotary crane system. The controller is trained by a real coded genetic algorithm, substantially simplifying the design of the controller. It is demonstrated that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.