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Data-Driven Control: Linear System Identification
Local Koopman Operators for Data-Driven Control of Robotic Systems
Data driven control of unknown nonlinear systems using extremum seeking control
Data-Driven Control: Change of Variables in Control Systems
Data-driven MPC: From linear to nonlinear systems with guarantees
Data-Driven Control: Balancing Example
Data-Driven Control: The Goal of Balanced Model Reduction
Data-Driven Control: Balanced Models with ERA
Data-Driven Approaches for Better Motion Control
Data-Driven Iterative Optimal Control for Switched Dynamical Systems
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Last Updated: September 25, 2026
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Summary
Associated with a CDC2017 publication "Paulo Tabuada, Wen-Loong Ma, Jessy Grizzle, and Aaron D. Ames, In this lecture, we describe the eigensystem realization algorithm (ERA) in detail, including step-by-step algorithmic instructions. Speaker: Professor Martin Guay, Queen's University, Canada. Prof. Dr.-Ing. Frank Allgöwer, University of Stuttgart, Germany. Presented by Cong Wang at SBRS 2014. The Stanford-Berkeley Robotics Symposium brought together roboticists from Stanford, ...
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