Haoyong Yu
National University of Singapore
262 Papers
1.3K Citations
Haoyong Yu is an academic researcher from National University of Singapore. The author has contributed to research in topics: Computer science & Adaptive control. The author has an hindex of 44, co-authored 262 publications. Previous affiliations of Haoyong Yu include Maebashi Institute of Technology & Keio University.
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Papers
Preliminary design analysis of a novel variable impedance compact compliant actuator
Haoyong Yu,S. M. Mizanoor Rahman,Chi Zhu +2 more
- 01 Dec 2011
TL;DR: A novel variable impedance compact compliant series elastic actuator (SEA) design for human-friendly robotics applications that overcomes the major limitations in the existing SEA design which requires a trade-off in the selection of spring constant.
10
Composite learning from model reference adaptive fuzzy control
Yongping Pan,Meng Joo Er,Lin Pan,Haoyong Yu +3 more
- 01 Nov 2015
TL;DR: The proposed model reference composite learning fuzzy control strategy can guarantee accurate function approximation under greatly reduced computational cost and has been verified by applying it to an control problem of aircraft wing rock.
9
Robustness analysis of composite adaptive robot control
Yongping Pan,Tairen Sun,Lin Pan,Haoyong Yu +3 more
- 28 May 2016
TL;DR: In this paper, robustness analysis of CAC for a class of arm-type robots formulated by Euler-Lagrange systems has been conducted and it is shown that CAC is still not robust against bounded perturbations without robust modifications.
9
Study on mathematic magnetic field model of rectangular coils for magnetic actuation
Shuang Song,Haoyong Yu,Hongliang Ren +2 more
- 03 May 2015
TL;DR: A mathematic magnetic field model of rectangular electromagnetic coils for magnetic actuation based on the Biot-Savart Law and superposition principle is presented and simulation results show the feasibility of the method.
9
A robust force controller design for series elastic actuators
Emre Sariyildiz,Haoyong Yu +1 more
- 01 Sep 2017
TL;DR: It is experimentally shown that high performance force control applications can be performed without requiring the precise dynamic models of the actuator and environment when the proposed robust force controller is implemented.