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A Versatile Framework for Data-Driven Control of Nonlinear Systems
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AI
DOI：10.1109/TAC.2025.3597243.png)
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Abstract
En 中文
This note aims to provide a systematic investigation of direct data-driven control, enriching the existing literature not by adding another isolated result, but rather by offering a unifying, versatile, and broad framework that enables the generation of novel results in this domain. We formulate the nonlinear design problem from a high-level perspective as a set of desired controlled systems and propose systematic procedures to synthesize data-driven control algorithms that meet the specified design requirements. Various examples are presented to demonstrate the applicability of the proposed approach and its ability to derive new insights and results, illustrating the novel contributions enabled by the framework.
Keywords:
Data-driven control
linear matrix inequalities
nonlinear control systems
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W