Robust command filter-based model predictive control for spacecraft rendezvous

The spacecraft rendezvous problem under external disturbances represents a significant and challenging research area. To enhance the accuracy of spacecraft rendezvous, this paper develops a model predictive control algorithm augmented by a function-adaptive law (FAL). The FAL is introduced to estimate and compensate for unknown disturbances in the aerospace environment effectively. A notable feature of this FAL is its integration with a robust command filtering (RCF) algorithm, which includes three key subtask modules: derivative excitation, noise suppression, and feedback correction. This meticulously designed structure enables the suppression of high-frequency components in the signal while accurately extracting its differential information. The paper provides a theoretical analysis of the recursive feasibility and stability of the designed model predictive controller and validates the controller’s effectiveness through a series of simulation experiments.