Load Swing Suppression for Rotary Crane System Using Direct Gradient Descent Controller Optimized by Genetic Algorithm

In this paper, we propose a control method for a rotary crane system using Direct Gradient Descent Control (DGDC) optimized by a genetic algorithm (GA). The rotary crane is known to be a class of nonholonomic system and the DGDC method is useful for the nonholonomic system control. However, the control performance of the DGDC strongly depends on the parameters of controller and the value of initial control inputs. Also, for usage of the DGDC, it is required to re-design iteratively the control parameters or the control inputs. We applied GA optimization to determine the sets of control parameters of the DGDC for the crane system. The parameters of the DGDC optimized by GA are not required to be re-designed. Simulation results show that the proposed method has higher control performance and has good robustness with noise and fluctuation of the initial states.