Adaptive hidden mode tracking control with input constraints and bounded disturbances

Sze Yong; Emilio Frazzoli

doi:10.1109/CDC.2016.7798435

Adaptive hidden mode tracking control with input constraints and bounded disturbances

Sze Yong, Emilio Frazzoli

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

1 Scopus citations

Abstract

In this paper, we develop an adaptive control approach for hidden mode tracking of uncertain hybrid systems in Brunovsky form that are subject to actuator input amplitude and rate constraints, as well as bounded disturbances. Our approach adapts to the parameters of the hidden mode, and relies on a systematic modification of the reference model to deal with input constraints and disturbances in a stable manner. Global tracking capability is shown for input-to-state stable systems, while for input-to-state unstable systems, the local regions of attraction are characterized. The effectiveness of our input-constrained hidden mode tracking approach is illustrated with a robot walking example.

Original language	English (US)
Title of host publication	2016 IEEE 55th Conference on Decision and Control, CDC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1235-1242
Number of pages	8
ISBN (Electronic)	9781509018376
DOIs	https://doi.org/10.1109/CDC.2016.7798435
State	Published - Dec 27 2016
Externally published	Yes
Event	55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States Duration: Dec 12 2016 → Dec 14 2016

Other

Other	55th IEEE Conference on Decision and Control, CDC 2016
Country/Territory	United States
City	Las Vegas
Period	12/12/16 → 12/14/16

ASJC Scopus subject areas

Artificial Intelligence
Decision Sciences (miscellaneous)
Control and Optimization

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10.1109/CDC.2016.7798435

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Yong, S & Frazzoli, E 2016, Adaptive hidden mode tracking control with input constraints and bounded disturbances. in 2016 IEEE 55th Conference on Decision and Control, CDC 2016., 7798435, Institute of Electrical and Electronics Engineers Inc., pp. 1235-1242, 55th IEEE Conference on Decision and Control, CDC 2016, Las Vegas, United States, 12/12/16. https://doi.org/10.1109/CDC.2016.7798435

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abstract = "In this paper, we develop an adaptive control approach for hidden mode tracking of uncertain hybrid systems in Brunovsky form that are subject to actuator input amplitude and rate constraints, as well as bounded disturbances. Our approach adapts to the parameters of the hidden mode, and relies on a systematic modification of the reference model to deal with input constraints and disturbances in a stable manner. Global tracking capability is shown for input-to-state stable systems, while for input-to-state unstable systems, the local regions of attraction are characterized. The effectiveness of our input-constrained hidden mode tracking approach is illustrated with a robot walking example.",

author = "Sze Yong and Emilio Frazzoli",

year = "2016",

month = dec,

day = "27",

doi = "10.1109/CDC.2016.7798435",

language = "English (US)",

pages = "1235--1242",

booktitle = "2016 IEEE 55th Conference on Decision and Control, CDC 2016",

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note = "55th IEEE Conference on Decision and Control, CDC 2016 ; Conference date: 12-12-2016 Through 14-12-2016",

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AU - Frazzoli, Emilio

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N2 - In this paper, we develop an adaptive control approach for hidden mode tracking of uncertain hybrid systems in Brunovsky form that are subject to actuator input amplitude and rate constraints, as well as bounded disturbances. Our approach adapts to the parameters of the hidden mode, and relies on a systematic modification of the reference model to deal with input constraints and disturbances in a stable manner. Global tracking capability is shown for input-to-state stable systems, while for input-to-state unstable systems, the local regions of attraction are characterized. The effectiveness of our input-constrained hidden mode tracking approach is illustrated with a robot walking example.

AB - In this paper, we develop an adaptive control approach for hidden mode tracking of uncertain hybrid systems in Brunovsky form that are subject to actuator input amplitude and rate constraints, as well as bounded disturbances. Our approach adapts to the parameters of the hidden mode, and relies on a systematic modification of the reference model to deal with input constraints and disturbances in a stable manner. Global tracking capability is shown for input-to-state stable systems, while for input-to-state unstable systems, the local regions of attraction are characterized. The effectiveness of our input-constrained hidden mode tracking approach is illustrated with a robot walking example.

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M3 - Conference contribution

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EP - 1242

BT - 2016 IEEE 55th Conference on Decision and Control, CDC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 55th IEEE Conference on Decision and Control, CDC 2016

Y2 - 12 December 2016 through 14 December 2016

ER -

Adaptive hidden mode tracking control with input constraints and bounded disturbances

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