In order to compensate disturbance and accomplish the stabilized tracking control for airborne platform mounted on multi-rotor unmanned aerial vehicle (MUAV), a self-adjusting tracking control method based on an improved disturbance observer (DOB) and radial basis function (RBF) neural network approximation is proposed. First, a compensated control is introduced into feedback loop in the structure of original disturbance observer, an improved disturbance observer is established based on velocity signals, and the ability of disturbance compensation and robustness are analyzed. Second, aiming at the compensation problem of nonlinear unknown disturbance, a method based on the RBF neural network (RBFNN) approximation properties is utilized. Finally, a composite compensation control structure is designed based on Lyapunov stability theory. The experimental results show that after applying the proposed method, the disturbance of airborne opto-electronic platform is compensated effectively. The proposed method has high precision and stable tracking control performance, and it can fully meet the requirement of airborne opto-electronic platform stability control.