Neuroadaptive Cooperative Control Without Velocity Measurement for Multiple Humanoid Robots under Full-State Constraints

Zhirong ZHANG; Yongduan SONG; Kai ZHAO

doi:10.1109/TIE.2018.2844791

Neuroadaptive Cooperative Control Without Velocity Measurement for Multiple Humanoid Robots under Full-State Constraints

Zhirong ZHANG
, Yongduan SONG^*
, Kai ZHAO

^*Corresponding author for this work

Research output: Journal Publications › Journal Article (refereed) › peer-review

62 Citations (Scopus)

Abstract

This paper studies the cooperative control problem of multiple humanoid robots handling a common payload in the presence of position and velocity constraints, unmeasurable velocity, as well as nonparametric uncertainties. By using a state observer to estimate the unmeasured velocity, a neuroadaptive output-feedback control scheme is developed, which by blending an error transformation with barrier Lyapunov function ensures that the full-state tracking error converges to a prescribed compact set around origin within a given finite time at a preassignable convergence rate. Furthermore, it is shown that all the signals in the closed-loop system are ultimately semiglobally uniformly bounded. Simulation results are verified to show the effectiveness and benefits of the proposed scheme.

Original language	English
Article number	8387772
Pages (from-to)	2956-2964
Number of pages	9
Journal	IEEE Transactions on Industrial Electronics
Volume	66
Issue number	4
Early online date	18 Jun 2018
DOIs	https://doi.org/10.1109/TIE.2018.2844791
Publication status	Published - Apr 2019
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 61773081 and in part by the Central University Fund under Grant 2018CDJDZ0009.

Keywords

Barrier Lyapunov function
error transformation
multiple humanoid robots
output feedback control

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10.1109/TIE.2018.2844791

Cite this

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title = "Neuroadaptive Cooperative Control Without Velocity Measurement for Multiple Humanoid Robots under Full-State Constraints",

abstract = "This paper studies the cooperative control problem of multiple humanoid robots handling a common payload in the presence of position and velocity constraints, unmeasurable velocity, as well as nonparametric uncertainties. By using a state observer to estimate the unmeasured velocity, a neuroadaptive output-feedback control scheme is developed, which by blending an error transformation with barrier Lyapunov function ensures that the full-state tracking error converges to a prescribed compact set around origin within a given finite time at a preassignable convergence rate. Furthermore, it is shown that all the signals in the closed-loop system are ultimately semiglobally uniformly bounded. Simulation results are verified to show the effectiveness and benefits of the proposed scheme.",

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AB - This paper studies the cooperative control problem of multiple humanoid robots handling a common payload in the presence of position and velocity constraints, unmeasurable velocity, as well as nonparametric uncertainties. By using a state observer to estimate the unmeasured velocity, a neuroadaptive output-feedback control scheme is developed, which by blending an error transformation with barrier Lyapunov function ensures that the full-state tracking error converges to a prescribed compact set around origin within a given finite time at a preassignable convergence rate. Furthermore, it is shown that all the signals in the closed-loop system are ultimately semiglobally uniformly bounded. Simulation results are verified to show the effectiveness and benefits of the proposed scheme.

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Neuroadaptive Cooperative Control Without Velocity Measurement for Multiple Humanoid Robots under Full-State Constraints

Abstract

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Keywords

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