Tengfei Tang

Dr. Tengfei Tang


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 August 2022 in Ocean Engineering
Verified
Journal Article
Closed access
LLLei Lei
Lei Lei
TTTengfei Tang
Tengfei Tang
YGYang Gang
Yang Gang
GJGuo Jing
Guo Jing

5 April 2020 in Structural and Multidisciplinary Optimization
Verified
Journal Article
Closed access
PDF file
TTTengfei Tang
Tengfei Tang
GYGang Yang
Gang Yang
DZDijia Zhang
Dijia Zhang
LLLei Lei
Lei Lei
BLBaoren Li
Baoren Li
LGLonglong Gao
Longlong Gao

28 October 2021 in Applied Sciences
Verified
Journal Article
Open access
PDF file
LHLiao Li hui
Liao Li hui
BLBaoren Li
Baoren Li
YWYuanyuan Wang
Yuanyuan Wang
TTTengfei Tang
Tengfei Tang
DZDijia Zhang
Dijia Zhang
YGYang gang
Yang gang
High dynamic performance of a deep-sea electric oil-filled joint actuator is an important premise to guarantee the working performance of an electric underwater manipulator. However, the unfavorable factors (i.e., extremely high water pressure, near freezing temperature) brought by the deep-sea working environment seriously affect the characteristic and dynamic performance of the electric oil-filled joint actuator, which mainly includes oil stirring viscos loss, output shaft dynamic seal loss, and core loss. In this paper, a novel observer-based robust control method named prescribed performance non-singular fast-terminal sliding-mode control (PP-NFTSMC-ESO) was synthesized for improving the dynamic performance of a deep-sea electric oil-filled joint actuator. The extended state observer (ESO) was employed to observe the unmeasured joint velocity signal and estimate the lumped uncertainties, while the prescribed performance function (PPF) was applied to constrain the instantaneous and steady-state performance of the trajectory-tracking error. The robust NFTSMC control method was then established by integrating the function of ESO and PPF through backstepping methodology. The stability of the proposed PP-NFTSMC-ESO strategy was analyzed and proved by the Lyapunov’s stability theory. It was proven that under the proposed controller, all the closed-loop signals are bounded and the trajectory tracking errors will converge to a small neighborhood of the origin with appropriate design parameters. The effectiveness of the proposed control scheme was illustrated by comparative simulation studies.