Trajectory tracking control for airships based on command-filtered slide mode control with neural network approximation

This paper proposes a new slide mode controller to address unmanned airships' trajectory tracking problem in the presence of unknown wind disturbance. Firstly, the nonlinear model of an airship is introduced. Secondly, a slide mode controller is designed to track the commanded trajectory, using a fast power rate reaching law(FPRRL). A newly designed command filter is adopted to avoid the aggressive adaptation. Furthermore, a radial basis function neural network(RBFNN) is employed to approximate the wind field, decreasing the tracking error caused by the disturbance. Stability analysis shows that the presented controller drives the tracking error to converge to a quite small region. Simulation results are provided to validate the satisfying performance of the proposed controller.