Active disturbance rejection control (ADRC) is widely used in airborne optoelectronic stabilization platforms due to its minimal reliance on the mathematical model of the controlled object. The extended state observer (ESO) is the core of ADRC, which treats internal parameter variations and external disturbances as total disturbances, observes the disturbances as extended states, and then compensates them into the control loop to eliminate their effects. However, the ESO can only achieve a precise estimation of constant or slowly varying disturbances. When the disturbance is periodically changing, satisfactory results cannot be obtained. In this paper, a generalized high-order extended state observer (GHOESO) is proposed to achieve the precise estimation of known frequency sinusoidal disturbance signals and improve disturbance suppression levels. Through numerical simulations, a traditional ESO and GHOESO are compared in terms of disturbance observation capability and disturbance suppression ability for single and compound disturbances based on our prior knowledge of disturbance frequency. The effectiveness of the proposed GHOESO method is verified. Finally, the algorithm is applied to an airborne optoelectronic stabilization platform for a 1°/1 Hz swing experiment on a space hexapod swing table. The experimental results demonstrate the superiority of the GHOESO proposed in this paper.

Due to long-term wear and attitude disturbance caused by shafting friction and other factors, the model parameters of the UAV-mounted optoelectronic platform are transformed, and the control accuracy and robustness of the platform are reduced. The traditional approach involves utilizing disturbance observers to observe disturbance values and subsequently reduce their impact on the system. However, when there is significant uncertainty in the model parameters, the application of this method is constrained. Therefore, a super-twisted sliding mode control based on predictive adaptive law (SSMC + PAL) (SSMPAL) is proposed. Firstly, to adapt to the impact of changes in platform structural parameters on the system and mitigate speed fluctuations, a predictive adaptive law is devised. Subsequently, a super-twisted sliding mode controller(SSMC) was developed, whose high-order performance effectively mitigates the chattering phenomenon associated with traditional sliding mode control strategies and minimizes the impact of observation errors stemming from significant model parameter uncertainties on system control accuracy. The convergence and robustness of the designed control strategy are proven using Lyapunov’s theorem. Finally, the effectiveness of the algorithm is verified using an actual UAV-mounted optoelectronic platform. The step response test results indicate that, compared to the disturbance observer control strategy, this method reduces the overshoot by 7.8% and significantly shortens the response time and transition process, demonstrating its superior dynamic response capability. Subsequent anti-disturbance and robustness tests further highlight the superiority of SSMPAL over disturbance observers in terms of anti-disturbance ability and stability, highlighting its significant engineering application value.