Robust Control, Feedback and Learning: Data-Driven Methods

2004 ◽  
Author(s):  
Michael G. Safonov
2021 ◽  
Vol 22 ◽  
pp. 32
Author(s):  
Agathe Reille ◽  
Victor Champaney ◽  
Fatima Daim ◽  
Yves Tourbier ◽  
Nicolas Hascoet ◽  
...  

Solving mechanical problems in large structures with rich localized behaviors remains a challenging issue despite the enormous advances in numerical procedures and computational performance. In particular, these localized behaviors need for extremely fine descriptions, and this has an associated impact in the number of degrees of freedom from one side, and the decrease of the time step employed in usual explicit time integrations, whose stability scales with the size of the smallest element involved in the mesh. In the present work we propose a data-driven technique for learning the rich behavior of a local patch and integrate it into a standard coarser description at the structure level. Thus, localized behaviors impact the global structural response without needing an explicit description of that fine scale behaviors.


2013 ◽  
Vol 198 ◽  
pp. 571-576 ◽  
Author(s):  
Arkadiusz Mystkowski

This paper discusses a nonlinear robust control design procedure to micro air vehicle that uses the singular value (μ) and μ-synthesis technique. The optimal robust control law that combines a linear parameters varying (LPV) of UAV (unmanned aerial vehicle) are realized by using serial connection of the Kestrel autopilot and the Gumstix microprocessor. Thus, the robust control feedback loops, which handle the uncertainty of aerodynamics derivatives, are used to ensure robustness stability of the UAV local dynamics in longitudinal and lateral control directions.


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