桥式起重机定位和防摆的RBF神经网络控制

It was proposed a radical basis function neural network (RNFNN) anti-swing and position control of overhead cranes considering the nonlinearity and uncertainty of the crane model,where two radial basis function neural network controller were designed to control the trolley position and load swing separately.The radial basis function neural network position controller was based on a simple square wave position reference trajectory to control the position and velocity of the trolley. The radial basis function neural network anti-swing controller was used to implement hanging rope swing angle and swing velocity decreases to zero when reaching the destination. Simulation results show that the presented conrtoller can realize positioning and anti-swaying simultaneously,and compared with linear quadratic regulator(LQR),this method is of good control performance and robust .