Youhao Hu

Orcid: 0000-0003-0320-452X

According to our database1, Youhao Hu authored at least 12 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
BifrostUMI: Bridging Robot-Free Demonstrations and Humanoid Whole-Body Manipulation.
CoRR, May, 2026

OmniUMI: Towards Physically Grounded Robot Learning via Human-Aligned Multimodal Interaction.
CoRR, April, 2026

2025
Thor: Towards Human-Level Whole-Body Reactions for Intense Contact-Rich Environments.
CoRR, October, 2025

2024
Fixed-Time Adaptive Sliding Mode Control for Vehicular Electronic Throttle With Actuator Saturation Using Extreme Learning Machine.
IEEE Trans. Veh. Technol., December, 2024

A Power-Boosted WPT System Using Both 1<sup>st</sup> and 3<sup>rd</sup> Harmonics and Decoupled Magnetic Couplers.
Proceedings of the 50th Annual Conference of the IEEE Industrial Electronics Society, 2024

2023
Maximum Efficiency Tracking of Wireless Power Transfer by Using Receiver-Side Variable Capacitors.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

Robust Speed Control for Wireless Motor Systems with Maximum Efficiency Point Tracking.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

Analysis of Self-Oscillation Frequency in an Inductive Power Transfer System.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

2022
Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine.
Neural Comput. Appl., 2022

Real-Time Control Systems with Applications in Mechatronics.
Proceedings of the Handbook of Real-Time Computing, 2022

2021
Adaptive Tracking Control of an Electronic Throttle Valve Based on Recursive Terminal Sliding Mode.
IEEE Trans. Veh. Technol., 2021

2020
Extreme-learning-machine-based FNTSM control strategy for electronic throttle.
Neural Comput. Appl., 2020


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