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We propose a robust sliding mode control (SMC) scheme for a class ofuncertain multi-input and multi-output (MIMO) nonlinear systems with the unknown external disturbance,the system uncertainty, and the backlash-like hysteresis. To tackle the continuous systemuncertainty, the radial basis function (RBF) neural network is employed to approximate it. Andthen, combine the unknown external disturbance, and the unknown neural network approximationerror with the affection caused by backlash-like hysteresis as a compounded disturbance which is estimatedusing the developed nonlinear disturbance observer. The robust sliding mode control basedon the nonlinear disturbance observer and RBF neural network is presented to track the desiredsystem output in the presence of the unknown system uncertainty, the external disturbance, andthe backlash-like hysteresis. Finally, the designed robust sliding mode control strategy is appliedto the near-space vehicle (NSV) attitude dynamics, and simulation results are given to illustrate theeffectiveness of the proposed sliding mode control approach.

Sliding Mode Control for a Class of Uncertain MIMO Nonlinear Systems with Application to Near-Space Vehicles