增强型模型预测控制：卫星敏捷性与计算复杂性之间的平衡
Augmented Model Predictive Control: A Balance between Satellite Agility and Computation Complexity
AI总结：
本文提出一种增强型MPC方法，在保持线性MPC计算简单性的同时实现非线性MPC的高性能，通过数值模拟和实验验证其在提升卫星敏捷性方面的有效性。
摘要：
敏捷地球观测卫星采用多个执行器以实现灵活的成像能力。尽管执行器技术显著提升了卫星的扭矩和动量，但针对提高卫星敏捷性的控制策略研究较少。本文比较了不同模型预测控制（MPC）形式，并引入一种增强型MPC方法，有效平衡敏捷性需求与硬件实现约束。所提方法在保持线性MPC计算简单性的同时实现了非线性MPC的高性能。通过数值模拟和物理实验验证了所提方法的有效性和可行性。
英文摘要：
Agile earth observation satellites employ multiple actuators to enable flexible and responsive imaging capabilities. While significant advancements in actuator technology have enhanced satellites' torque and momentum, relatively little attention has been given to control strategies specifically tailored to improve satellite agility. This paper provides a comparative analysis of different Model Predictive Control (MPC) formulations and introduces an augmented-MPC method that effectively balances agility requirements with hardware implementation constraints. The proposed method achieves the high-performance characteristics of nonlinear MPC while preserving the computational simplicity of linear MPC. Numerical simulations and physical experiments are conducted to validate the effectiveness and feasibility of the proposed approach.
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