Learning Theory Convergence Rates for Observers and Controllers in Native Space Embedding

Author:

Burns John1,Kurdila Andrew2,Oesterheld Derek3,Stilwell Dan3,Wang Haoran2

Affiliation:

1. Virginia Tech,Department of Mathematics,Blacksburg,VA,USA,24060

2. Virginia Tech,Mechanical Engineering Department,Blacksburg,VA,USA,24060

3. Virginia Tech,Bradley Department of Electrical and Computer Engineering,Blacksburg,VA,USA,24060

Funder

Office of Naval Research

Publisher

IEEE

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Newton Bases and Event-Triggered Adaptive Control in Native Spaces;2024 American Control Conference (ACC);2024-07-10

2. The Power Function for Adaptive Control in Native Space Embedding;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

3. A Model Reference Adaptive Controller Based on Operator-Valued Kernel Functions;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

4. Comparison of Data-Driven Model Reference Adaptive Control Methods for Attitude Control of Autonomous Underwater Vehicles;OCEANS 2023 - MTS/IEEE U.S. Gulf Coast;2023-09-25

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