The principle of least action is one of the most fundamental physical principle. It says that among all possible motions connecting two points in a phase space, the system will exhibit those motions which extremise an action functional. Many qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equations, are related to the existence of an action functional. Incorporating variational structure into learning algorithms for dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features with the exact physical system. In this paper we show how to incorporate variational principles into trajectory predictions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position data of observed trajectories. Velocities or conjugate momenta do {\em not} need to be observed or approximated and {\em no} prior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward error analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the learned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this, we introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of variational backward error analysis. (3) Finally, we introduce a method to perform system identification from position observations only, based on variational backward error analysis.
翻译:最小行动的原则是最基本的物理原则之一。 它指出, 在连接一个阶段空间中两个点的所有可能动议中, 系统将展示那些扩展行动功能的动作。 动态系统的许多质量特征, 如保护法和能源平衡方程式的存在, 都与行动功能的存在有关。 因此, 将差异结构纳入动态系统的学习算法至关重要, 以确保所学模型与精确的物理系统具有重要特征。 在本文中, 我们展示了如何将变异原则纳入所学动态系统的轨迹预测中。 这项工作的新颖之处是:(1) 我们的技术仅依赖于所观察到的轨迹的离散位置数据。 需要观察速度或共振时钟的瞬间平衡等与行动功能的存在有关。 因此, 将变异结构纳入动态系统的学习算法至关重要, 以确保所学模型与准确的物理系统共享重要特征。 此外, 我们的技术在从所学的系统计算轨迹轨迹时, 只能弥补离散错误。 当我们进行中度到大型的后向定位观察时, 使用一个快速的后向分析方法来分析, 进行我们进行后向定位分析, 进行后向变式分析, 需要我们进行后向式分析。 进行后向分析, 进行后向分析。 进行后向分析。 进行后向分析时, 进行后向分析时我们进行后向式分析, 进行后向式分析, 进行后向式分析。