用实时非线性模型预测控制解决双摆的快速起摆问题

Real-Time Model Predictive Control for the Swing-Up Problem of an Underactuated Double Pendulum

• 基于实时非线性模型预测控制，动态规划最优轨迹
• 在任意初始状态下均能稳定起摆，抗干扰能力强
• 适合需要高精度、实时响应的欠驱动系统控制场景

第三届人工智能奥林匹克赛与RealAIGym竞赛提出了一个挑战：设计一种全局策略，能够从状态空间中任意配置出发，将欠驱动的两杆系统Acrobot和/或Pendubot完成起摆并稳定。本文提出一种基于最优控制的实时非线性模型预测控制（MPC）方法。结果表明，该控制器具备优异性能与鲁棒性，能可靠应对各种扰动，适用于复杂动态系统的实时控制任务。

原文摘要 · Abstract (English)

The 3rd AI Olympics with RealAIGym competition poses the challenge of developing a global policy that can swing up and stabilize an underactuated 2-link system Acrobot and/or Pendubot from any configuration in the state space. This paper presents an optimal control-based approach using a real-time Nonlinear Model Predictive Control (MPC). The results show that the controller achieves good performance and robustness and can reliably handle disturbances.

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