AI RESEARCH
Federated Learning for Data-Driven Feedforward Control: A Case Study on Vehicle Lateral Dynamics
arXiv CS.LG
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ArXi:2503.02693v2 Announce Type: replace In many control systems, tracking accuracy can be enhanced by combining (data-driven) feedforward (FF) control with feedback (FB) control. However, designing effective data-driven FF controllers typically requires large amounts of high-quality data and a dedicated design-of-experiment process. In practice, relevant data are often distributed across multiple systems, which not only