Characterizing the Predictive Accuracy of Dynamic Mode Decomposition for Data-Driven Control
Dynamic mode decomposition (DMD) is a versatile approach that enables the construction of low-order models from data. Controller design tasks based on such models require estimates and guarantees on predictive accuracy. In this work, we provide a theoretical analysis of DMD model errors that reveals impact of model order and data availability. The analysis also establishes conditions under which DMD models can be made asymptotically exact. We verify our results using a 2D diffusion system.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Dynamic Mode Decomposition for Financial Trading Strategies
We demonstrate the application of an algorithmic trading strategy based upon the recently developed dynamic mode decomposition (DMD) on portfolios of financial data. The method is capable of characterizing complex dynami…
Algorithmic TradingOnline Kernel Dynamic Mode Decomposition for Streaming Time Series Forecasting with Adaptive Windowing
Real-time forecasting from streaming data poses critical challenges: handling non-stationary dynamics, operating under strict computational limits, and adapting rapidly without catastrophic forgetting. However, many exis…
Time Series ForecastingConvex Bounds on the Softmax Function with Applications to Robustness Verification
The softmax function is a ubiquitous component at the output of neural networks and increasingly in intermediate layers as well. This paper provides convex lower bounds and concave upper bounds on the softmax function, w…
Compressed Dynamic Mode Decomposition for Background Modeling
We introduce the method of compressed dynamic mode decomposition (cDMD) for background modeling. The dynamic mode decomposition (DMD) is a regression technique that integrates two of the leading data analysis methods in …
compressed sensingComputational EfficiencyGPUData-driven Model Predictive Control Method for DFIG-based Wind Farm to Provide Primary Frequency Regulation Service
As wind power penetration increases, the wind farms are required by newly released grid codes to provide frequency regulation service. The most critical challenge is how to formulate the dynamic model of wind farm for dy…
Dimensionality ReductionModel Predictive Control