Andrew J. Kurdila

30 papers C 7Journal 14Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`book`	Data-Driven, Nonparametric, Adaptive Control Theory Andrew J. Kurdila, Andrea L'Afflitto, John A. Burns
2025	J	`jnl`	Functional Uncertainty Classes, Nonparametric Adaptive Contro Functional Uncertainty Classes for Nonparametric Adaptive Control: the Curse of Dimensionality. CoRR Haoran Wang, Shengyuan Niu, Henry Moon, Ian Willebeek-LeMair, Andrew J. Kurdila, Andrea L'Afflitto, Daniel J. Stilwell
2025	J	`jnl`	Robust Adaptive Backstepping Control Over Native Spaces. IEEE Control. Syst. Lett. Giorgio A. Orlando, Andrea L'Afflitto, Andrew J. Kurdila
2024	C	`conf`	Newton Bases and Event-Triggered Adaptive Control in Native Spaces. ACC Nathan Powell, Andrew J. Kurdila, Andrea L'Afflitto, Haoran Wang, Jia Guo
2024	J	`jnl`	Nonparametric adaptive control in native spaces: A DPS framework (Part I). Annu. Rev. Control. Andrew J. Kurdila, Andrea L'Afflitto, John A. Burns, Haoran Wang
2024	J	`jnl`	Nonparametric adaptive control in native spaces: Finite-dimensional implementations, Part II. Annu. Rev. Control. Andrew J. Kurdila, Andrea L'Afflitto, John A. Burns, Haoran Wang
2023	—	`conf`	A Model Reference Adaptive Controller Based on Operator-Valued Kernel Functions. CDC Derek I. Oesterheld, Daniel J. Stilwell, Andrew J. Kurdila, Jia Guo
2023	C	`conf`	Error Bounds for Native Space Embedding Observers with Operator-Valued Kernels. ACC John A. Burns, Jia Guo, Andrew J. Kurdila, Sai Tej Paruchuri, Haoran Wang
2023	J	`jnl`	MRAC With Adaptive Uncertainty Bounds via Operator-Valued Reproducing Kernels. IEEE Control. Syst. Lett. Haoran Wang, Brian Scurlock, Nathan Powell, Andrea L'Afflitto, Andrew J. Kurdila
2023	J	`jnl`	Partial Persistence of Excitation in RKHS Embedded Adaptive Estimation. IEEE Trans. Autom. Control. Jia Guo, Sai Tej Paruchuri, Andrew J. Kurdila
2023	—	`conf`	The Power Function for Adaptive Control in Native Space Embedding. CDC Haoran Wang, Nathan Powell, Andrea L'Afflitto, Andrew J. Kurdila, John A. Burns
2022	—	`conf`	Approximation of Koopman Operators: Irregular Domains and Positive Orbits. CDC Nathan Powell, Roger Liu, Jia Guo, Sai Tej Paruchuri, John A. Burns, Boone Estes, Andrew J. Kurdila
2022	C	`conf`	Collaborative Persistent Excitation in RKHS Embedded Adaptive Estimation with Consensus. ACC Jia Guo, Fumin Zhang, Andrew J. Kurdila
2022	J	`jnl`	Koopman Methods for Estimation of Animal Motions over Unknown, Regularly Embedded Submanifolds. CoRR Nathan Powell, Bowei Liu, Andrew J. Kurdila
2022	C	`conf`	Koopman Methods for Estimation of Motion over Unknown, Regularly Embedded Submanifolds. ACC Nathan Powell, Bowei Liu, Andrew J. Kurdila
2021	J	`jnl`	Strictly Decentralized Adaptive Estimation of External Fields using Reproducing Kernels. CoRR Jia Guo, Michael E. Kepler, Sai Tej Paruchuri, Haoran Wang, Andrew J. Kurdila, Daniel J. Stilwell
2020	—	`conf`	Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds. CDC Jia Guo, Sai Tej Paruchuri, Andrew J. Kurdila
2020	J	`jnl`	Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds. CoRR Jia Guo, Sai Tej Paruchuri, Andrew J. Kurdila
2020	—	`conf`	Intrinsic and Extrinsic Approximation of Koopman Operators over Manifolds. CDC Sai Tej Paruchuri, Jia Guo, Michael E. Kepler, Tim Ryan, Haoran Wang, Andrew J. Kurdila, Daniel J. Stilwell
2020	J	`jnl`	Intrinsic and Extrinsic Approximation of Koopman Operators over Manifolds. CoRR Sai Tej Paruchuri, Jia Guo, Michael E. Kepler, Tim Ryan, Haoran Wang, Andrew J. Kurdila, Daniel J. Stilwell
2020	—	`conf`	Learning Theory for Estimation of Animal Motion Submanifolds. CDC Nathan Powell, Andrew J. Kurdila
2020	C	`conf`	Persistence of Excitation in Uniformly Embedded Reproducing Kernel Hilbert (RKH) Spaces. ACC Jia Guo, Sai Tej Paruchuri, Andrew J. Kurdila
2020	J	`jnl`	RKHS Embedding for Estimating Nonlinear Piezoelectric Systems. CoRR Sai Tej Paruchuri, Jia Guo, Andrew J. Kurdila
2019	J	`jnl`	Adaptive estimation for nonlinear systems using reproducing kernel Hilbert spaces. Adv. Comput. Math. Parag Bobade, Suprotim Majumdar, Savio Pereira, Andrew J. Kurdila, John B. Ferris
2019	—	`conf`	Multi-agent adaptive estimation with consensus in reproducing kernel Hilbert spaces. ECC Parag Bobade, Dimitra Panagou, Andrew J. Kurdila
2019	J	`jnl`	Persistence of Excitation in Reproducing Kernel Hilbert Spaces, Positive Limit Sets, and Smooth Manifolds. CoRR Andrew J. Kurdila, Jia Guo, Sai Tej Paruchuri, Parag Bobade
2017	J	`jnl`	Adaptive Estimation for Nonlinear Systems using Reproducing Kernel Hilbert Spaces. CoRR Parag Bobade, Suprotim Majumdar, Savio Pereira, Andrew J. Kurdila, John B. Ferris
2017	C	`conf`	Adaptive estimation in reproducing kernel Hilbert spaces. ACC Parag Bobade, Suprotim Majumdar, Savio Pereira, Andrew J. Kurdila, John B. Ferris
2016	—	`conf`	Error estimates for multiwavelet approximations of a class of history dependent operators. CDC Shirin Dadashi, Parag Bobade, Andrew J. Kurdila
2010	C	`conf`	Near-Optimal Approximation Rates for Distribution Free Learning with Exponentially, Mixing Observations. ACC Andrew J. Kurdila, Bin Xu