Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and Benchmarks
Flow map learning (FML), in conjunction with deep neural networks (DNNs), has shown promises for data driven modeling of unknown dynamical systems. A remarkable feature of FML is that it is capable of producing accurate predictive models for partially observed systems, even when their exact mathematical models do not exist. In this paper, we present an overview of the FML framework, along with the important computational details for its successful implementation. We also present a set of well defined benchmark problems for learning unknown dynamical systems. All the numerical details of these problems are presented, along with their FML results, to ensure that the problems are accessible for cross-examination and the results are reproducible.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Learning Stochastic Dynamical System via Flow Map Operator
We present a numerical framework for learning unknown stochastic dynamical systems using measurement data. Termed stochastic flow map learning (sFML), the new framework is an extension of flow map learning (FML) that was…
MUSE: An Interactive Meta-Agent for Understanding and Steering LLM-powered Data Science Systems
Recent advances in large language models have enabled a new class of agentic data science systems that allow users to complete complex data science workflows through natural language. Although these systems can significa…
Model-Free Output Feedback Stabilization via Policy Gradient Methods
Stabilizing a dynamical system is a fundamental problem that serves as a cornerstone for many complex tasks in the field of control systems. The problem becomes challenging when the system model is unknown. Among the Rei…
Reinforcement LearningModeling Unknown Stochastic Dynamical System via Autoencoder
We present a numerical method to learn an accurate predictive model for an unknown stochastic dynamical system from its trajectory data. The method seeks to approximate the unknown flow map of the underlying system. It e…
DecoderStability/instability study of density systems and control law design
The paper considers some class of dynamical systems that called density systems. For such systems the derivative of quadratic function depends on so-called density function. The density function is used to set the proper…