Discrete sliding mode control for nonlinear systems with unknown inputs and random noise

The discrete sliding mode tracking control problem of nonlinear systems with unknown inputs and random noise is addressed in this paper. The objective is to design an Unknown Input Observer (UIO) based on the Extended Kalman Filter (EKF) such that the state vector of the whole system can be estimated and the decoupling of the disturbance terms can be achieved. Firstly, the state feedback matrix is solved in conjunction with the Extended Kalman Filter algorithm to minimise the covariance of the output residual signals, which in turn enhances the robustness of the system against random noise. Then, referring to the method of equivalent control and the state information estimated by the improving unknown input observer, we designed the discrete sliding mode controller. Finally, emulation experiments are carried out and the simulation results show the effectiveness and feasibility of the algorithms in this paper.