Abstract
In this paper we propose a neural network as a controller (NC) for suppression of load swing with disturbance like a gust in a rotary crane system. The rotary crane system has structure which rotates around the vertical axis. Then, the rotary crane system is a nonholonomic system. In general, it is difficult for nonholonomic system to design the classical control method using a static continuous state feedback law. So, it is necessary for nonholonomic system to design a time-varying feedback controller or a discontinuous feedback controller. Previous research had been successful in constructing the suppression controller of the load swing with a single initial rotation angle and three initial rotation angles when a gust occurred. The NC optimized by genetic algorithm (GA) had good control performance, but could not stabilize the load swing in the untrained condition. The control purpose of this paper is to improve the performance of the NC optimized by GA when the gust occurred at random.
