Suspension gravity offloading system with event-triggered ESO-based robust MPC

For space missions such as extraterrestrial sample collection, robotic rover exploration, and astronaut landings, the complex terrain and diverse gravitational environments make ground-based micro-low-gravity experimental systems essential for testing and validating spacecraft performance as well as supporting astronaut training. The suspended gravity unloading (SGO) system is a key device commonly used to simulate micro-low-gravity environments. However, the SGO system faces challenges due to model uncertainty and external disturbances, which limit improvements in control accuracy. To effectively address these issues, this paper proposes an adaptive extended state observer (ESO)-based dynamic event-triggered robust model predictive control (MPC) strategy for SGO system control. Firstly, the adaptive ESO effectively estimates the system's unmodeled dynamics and external disturbances. By integrating ESO-derived observations with the nominal model, an improved predictive model is developed. Secondly, the dynamic event-triggered (ET) mechanism significantly alleviates the computational burden of MPC. Finally, comparative numerical simulations and experimental validations are conducted to verify the effectiveness and superiority of the proposed control framework.