Abstract: Abstract: A nonsingular and fast terminal sliding mode controller based on the Chebyshev neural network (CNN) is designed for the next-generation smart imaging satellite, whose ground targets and ground trace are not parallel. First, the specific method of attitude adjustment for smart imaging mode is studied to get the desired attitude angle and angular velocity. According to the t racking error dynamics and kinematics described by unit quaternion error, a nonsingular and fast terminal sliding mode controller is derived. Considering the disturbance rejection, a Cheby-shev neural network whose basis functions are implemented using only desired signals is introduced to approximate the general disturbance which efficiently weaken the chattering inherent in sliding mode structure. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated disturbance, a switch function is applied to generate a switching between the adaptive neural network control and the robust controller. Finally, numerical simulations on the attitude tracking control of spacecraft in the presence of environmental disturbance and parameters uncertainties are performed, whose results show the designed control scheme can meet the requirements of control precision for the smart imaging with fast convergence speed and good robustness. The system can stabilize within and the precision of attitude angle and angular velocity is and ，respectively.

Key words: Key words: remote sensing, attitude tracking, sliding mode control, Chebyshev neural network (CNN), Lyapunov methods