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Tokamak Current Profile Regulation Using Nonlinear Infinite-dimensional Control
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Aug 1, 2022
Tokamak Current Profile Regulation Using Nonlinear Infinite-dimensional Control
Adaptive estimation of external fields in reproducing kernel Hilbert spaces
This article studies the distributed parameter system that governs adaptive estimation by mobile sensor networks of external fields in …
Jia Guo, Michael E Kepler, Sai Tej Paruchuri, Hoaran Wang, Andrew J Kurdila, Daniel J Stilwell
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Approximation of Discrete and Orbital Koopman Operators over Subsets and Manifolds
This paper describes a general approach for the construction of approximations of the Koopman operator associated with deterministic …
Andrew J Kurdila, Sai Tej Paruchuri, Nathan Powell, Jia Guo, Parag Bobade, Boone Estes, Haoran Wang
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Kernel center adaptation in the reproducing kernel Hilbert space embedding method
The performance of adaptive estimators that employ embedding in reproducing kernel Hilbert spaces (RKHS) depends on the choice of the …
Sai Tej Paruchuri, Jia Guo, Andrew Kurdila
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Sufficient conditions for parameter convergence over embedded manifolds using kernel techniques
The persistence of excitation (PE) condition is suf- ficient to ensure parameter convergence in adaptive estimation problems. Recent …
Sai Tej Paruchuri, Jia Guo, Andrew J Kurdila
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Lyapunov-based Safety Factor Control With Actuator Saturation
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Jun 1, 2021
Lyapunov-based Safety Factor Control With Actuator Saturation
Strictly Decentralized Adaptive Estimation of External Fields using Reproducing Kernels
This paper describes an adaptive method in continuous time for the estimation of external fields by a team of N agents. The agents i …
Jia Guo, Michael E Kepler, Sai Tej Paruchuri, Haoran Wang, Andrew J Kurdila, Daniel J Stilwell
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Approximations of the reproducing kernel hilbert space (rkhs) embedding method over manifolds
Abstract— The reproducing kernel Hilbert space (RKHS) embedding method is a recently introduced estimation approach that seeks to …
Jia Guo, Sai Tej Paruchuri, Andrew J Kurdila
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Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds
The reproducing kernel Hilbert space (RKHS) embedding method is a recently introduced estimation approach that seeks to identify the …
Jia Guo, Sai Tej Paruchuri, Andrew J Kurdila
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Intrinsic and Extrinsic Approximation of Koopman Operators over Manifolds
This paper derives rates of convergence of certain approximations of the Koopman operators that are associated with discrete, …
Sai Tej Paruchuri, Jia Guo, Michael Kepler, Tim Ryan, Haoran Wang, Andrew J Kurdila, Daniel Stilwell
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