In this paper, an adaptive sliding mode control algorithm based on friction compensation utilizing neural network (NN) is designed for an opto-electronic tracking system under the circumstance of friction and external disturbance. Since neural networks can approximate any nonlinear function, the developed NN controller can approximate the nonlinear friction which is integrated into the adaptive sliding mode control system in the Lyapunov framework. The adaptive sliding mode controller with friction compensation can effectively reduce the effects of nonlinear friction and external disturbance of the opto-electronic tracking system utilizing neural network approximations. The stability of the proposed method is guaranteed according to Lyapunov criterion. Simulation and experimental validation results for a nonlinear LuGre dynamic model of the opto-electronic tracking system are provided to validate the effectiveness of the proposed control method.