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Total Size:
10.2 MB
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94742F172A3A887A21A99F9E8E2D2437688D5A7D
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June 10, 2025, 12:55 p.m.
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(Last updated: June 11, 2025, 11:02 a.m.)
| File | Size |
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| ['Kurdila A. Data-Driven, Nonparametric, Adaptive Control Theory 2025.pdf'] | 0 bytes |
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| Uploaded by andryold1 | Size 10.2 MB | Health [ 37 /38 ] | Added 2025-06-10 |
NOTE
SOURCE: Kurdila A. Data-Driven, Nonparametric, Adaptive Control Theory 2025
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COVER

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MEDIAINFO
Textbook in PDF format Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties. The methods proposed enforce satisfactory trajectory tracking despite functional uncertainties in the plant model. The book employs the properties of reproducing kernel Hilbert (native) spaces to characterize both the functional space of uncertainties and the controller's performance. Classical control systems are extended to broader classes of problems and more informative characterizations of the controllers’ performances are attained
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