-
公开(公告)号：EP3772707A1
公开(公告)日：2021-02-10
申请号：EP19190105.7
申请日：2019-08-05
摘要： A system and computer-implemented method are provided for training a dynamics model to learn the dynamics of a physical system. In particular, the dynamics model may be learned to be able to infer a future state of the physical system and/or its environment based on a current state of the physical system and/or its environment. The learned dynamics model is inherently globally stable. Namely, instead of learning a dynamics model and attempting to separately verify its stability, the learnable dynamics model comprises a learnable Lyapunov function which is jointly learned together with the nominal dynamics of the physical system. Accordingly, the learned dynamics model is highly suitable for real-life applications in which a physical system may assume a state which was unseen during training as the learned dynamics model is inherently globally stable.
搜索结果
1 条记录 (耗时 0.01 秒)
筛选
AND
AND
过滤
NOT
NOT
扫码加群
