An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty

Dong Liang Chen; G-P Liu

doi:10.1109/ASCC.2017.8287304

An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty

Dong Liang Chen, G-P Liu

Faculty of Computing, Engineering and Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

In this paper, an adaptive control allocation algorithm is proposed for nonlinear autonomous vehicles. Parameter uncertainty of effectors is considered in the design of allocation algorithm. By designing a nonlinear parameter estimator, it needs not to measure the control moments, i.e., forces and torques. Sensors and corresponding supporting devices to measure and transit the control moments are not needed, thus the overall cost of the control system is reduced, and the hardware system is simplified in implementation. Stability of the overall system is analyzed utilizing the Lyapunov method and sufficient conditions are derived. Digital simulation based on a spacecraft simulator is implemented. The results of the simulation validate the effectiveness of the control scheme.

Original language	English
Title of host publication	2017 Asian Control Conference, ASCC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	982-987
Number of pages	6
Volume	2018-January
ISBN (Electronic)	9781509015733
DOIs	https://doi.org/10.1109/ASCC.2017.8287304
Publication status	Published - 7 Feb 2018
Event	2017 11th Asian Control Conference, ASCC 2017 - Gold Coast, Australia Duration: 17 Dec 2017 → 20 Dec 2017

Conference

Conference	2017 11th Asian Control Conference, ASCC 2017
Country/Territory	Australia
City	Gold Coast
Period	17/12/17 → 20/12/17

Access to Document

10.1109/ASCC.2017.8287304

ChenDL-ASCC2017Accepted author manuscript, 946 KB

1 Conference contribution

Multi-hop consensus for high-order integrator multi-agent systems
Li, C. J. & Liu, G-P., 7 Feb 2018, 2017 Asian Control Conference, ASCC 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January. p. 1871-1876 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Cite this

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title = "An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty",

abstract = "In this paper, an adaptive control allocation algorithm is proposed for nonlinear autonomous vehicles. Parameter uncertainty of effectors is considered in the design of allocation algorithm. By designing a nonlinear parameter estimator, it needs not to measure the control moments, i.e., forces and torques. Sensors and corresponding supporting devices to measure and transit the control moments are not needed, thus the overall cost of the control system is reduced, and the hardware system is simplified in implementation. Stability of the overall system is analyzed utilizing the Lyapunov method and sufficient conditions are derived. Digital simulation based on a spacecraft simulator is implemented. The results of the simulation validate the effectiveness of the control scheme.",

author = "Chen, {Dong Liang} and G-P Liu",

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doi = "10.1109/ASCC.2017.8287304",

language = "English",

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booktitle = "2017 Asian Control Conference, ASCC 2017",

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Chen, DL & Liu, G-P 2018, An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty. in 2017 Asian Control Conference, ASCC 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 982-987, 2017 11th Asian Control Conference, ASCC 2017, Gold Coast, Australia, 17/12/17. https://doi.org/10.1109/ASCC.2017.8287304

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N2 - In this paper, an adaptive control allocation algorithm is proposed for nonlinear autonomous vehicles. Parameter uncertainty of effectors is considered in the design of allocation algorithm. By designing a nonlinear parameter estimator, it needs not to measure the control moments, i.e., forces and torques. Sensors and corresponding supporting devices to measure and transit the control moments are not needed, thus the overall cost of the control system is reduced, and the hardware system is simplified in implementation. Stability of the overall system is analyzed utilizing the Lyapunov method and sufficient conditions are derived. Digital simulation based on a spacecraft simulator is implemented. The results of the simulation validate the effectiveness of the control scheme.

AB - In this paper, an adaptive control allocation algorithm is proposed for nonlinear autonomous vehicles. Parameter uncertainty of effectors is considered in the design of allocation algorithm. By designing a nonlinear parameter estimator, it needs not to measure the control moments, i.e., forces and torques. Sensors and corresponding supporting devices to measure and transit the control moments are not needed, thus the overall cost of the control system is reduced, and the hardware system is simplified in implementation. Stability of the overall system is analyzed utilizing the Lyapunov method and sufficient conditions are derived. Digital simulation based on a spacecraft simulator is implemented. The results of the simulation validate the effectiveness of the control scheme.

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M3 - Conference contribution

AN - SCOPUS:85047550915

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EP - 987

BT - 2017 Asian Control Conference, ASCC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

An adaptive control allocation algorithm for nonlinear vehicles with parameter uncertainty

Abstract

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Research output

Multi-hop consensus for high-order integrator multi-agent systems

Cite this