Non-Singular Fixed-Time Sliding Mode Control for Unknown-Dynamics Manipulators Interacting with Environment

In this paper, a robust fixed-time controller is de-signed for manipulators with unknown dynamics while interacting with environment. To realize compliance of the manipulator to the environment, an admittance model is adopted in the system. In the controller design, a non-singular sliding mode torque is introduced to achieve fixed-time convergence of the system state, so that the system has better tracking performance and faster response to external interaction than that using the traditional terminal sliding mode method. As for the unknown dynamics of the manipulator, radial basis function neural networks are developed to approximate the parameters in the dynamics. At last, simulation studies are conducted to verify the effectiveness of the proposed method.