带有事件触发的基于eso的稳健MPC的悬挂重力卸载系统。

IF 6.5
Huixing Yan, Hongqian Lu, Yefeng Yang, Tao Huang, Yanming Fu
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引用次数: 0

摘要

对于地外样本采集、机器人探测器探测和宇航员着陆等太空任务,复杂的地形和多样化的重力环境使得地面微低重力实验系统对于测试和验证航天器性能以及支持宇航员训练至关重要。悬浮式重力卸载系统是模拟微低重力环境的关键设备。然而,SGO系统面临着模型不确定性和外部干扰的挑战,这限制了控制精度的提高。为了有效地解决这些问题,本文提出了一种基于自适应扩展状态观测器(ESO)的动态事件触发鲁棒模型预测控制(MPC)策略用于SGO系统控制。首先,自适应ESO有效地估计了系统未建模的动力学和外部干扰。通过将eso的观测数据与名义模型相结合,建立了一个改进的预测模型。其次,动态事件触发(ET)机制显著减轻了MPC的计算负担。最后,通过对比数值仿真和实验验证,验证了所提控制框架的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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