Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay

Jing Na; Guido Herrmann; Xuemei Ren; Phil Barber

doi:10.1109/CDC.2009.5399674

Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay

Jing Na, Guido Herrmann, Xuemei Ren, Phil Barber

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

Abstract

This paper proposes an adaptive observer for discrete-time MIMO systems with unknown nonlinear dynamics and time-delay. The case that the system output equation has time-delay and nonlinearities is also studied. By using a high-order neural network (HONN), the exact system model, Lipschitz or norm-boundedness assumptions of unknown nonlinearities are not required. Other constraints used in neural-based observer design, i.e., strictly positive real (SPR) or matching conditions, are also removed. Applicability of the presented scheme is verified by simulation.

Original language	English
Title of host publication	Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
Publisher	IEEE
Pages	6137-6142
Number of pages	6
ISBN (Print)	9781424438716
DOIs	https://doi.org/10.1109/CDC.2009.5399674
Publication status	Published - 2009

Keywords

MIMO
Delay effects
Delay estimation
Neural networks
Uncertainty
Observers
Nonlinear dynamical systems
Nonlinear equations
Robustness
State estimation

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10.1109/CDC.2009.5399674

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@inproceedings{1916a37ab43243cab995fd45c522b577,

title = "Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay",

abstract = "This paper proposes an adaptive observer for discrete-time MIMO systems with unknown nonlinear dynamics and time-delay. The case that the system output equation has time-delay and nonlinearities is also studied. By using a high-order neural network (HONN), the exact system model, Lipschitz or norm-boundedness assumptions of unknown nonlinearities are not required. Other constraints used in neural-based observer design, i.e., strictly positive real (SPR) or matching conditions, are also removed. Applicability of the presented scheme is verified by simulation.",

keywords = "MIMO, Delay effects, Delay estimation, Neural networks, Uncertainty, Observers, Nonlinear dynamical systems, Nonlinear equations, Robustness, State estimation",

author = "Jing Na and Guido Herrmann and Xuemei Ren and Phil Barber",

note = "Name and Venue of Event: Shanghai Conference Organiser: IEEE",

year = "2009",

doi = "10.1109/CDC.2009.5399674",

language = "English",

isbn = "9781424438716",

pages = "6137--6142",

booktitle = "Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference",

publisher = "IEEE",

address = "United States",

}

Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay. / Na, Jing; Herrmann, Guido; Ren, Xuemei et al.
Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference. IEEE, 2009. p. 6137-6142.

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

TY - GEN

T1 - Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay

AU - Na, Jing

AU - Herrmann, Guido

AU - Ren, Xuemei

AU - Barber, Phil

N1 - Name and Venue of Event: Shanghai Conference Organiser: IEEE

PY - 2009

Y1 - 2009

N2 - This paper proposes an adaptive observer for discrete-time MIMO systems with unknown nonlinear dynamics and time-delay. The case that the system output equation has time-delay and nonlinearities is also studied. By using a high-order neural network (HONN), the exact system model, Lipschitz or norm-boundedness assumptions of unknown nonlinearities are not required. Other constraints used in neural-based observer design, i.e., strictly positive real (SPR) or matching conditions, are also removed. Applicability of the presented scheme is verified by simulation.

AB - This paper proposes an adaptive observer for discrete-time MIMO systems with unknown nonlinear dynamics and time-delay. The case that the system output equation has time-delay and nonlinearities is also studied. By using a high-order neural network (HONN), the exact system model, Lipschitz or norm-boundedness assumptions of unknown nonlinearities are not required. Other constraints used in neural-based observer design, i.e., strictly positive real (SPR) or matching conditions, are also removed. Applicability of the presented scheme is verified by simulation.

KW - MIMO

KW - Delay effects

KW - Delay estimation

KW - Neural networks

KW - Uncertainty

KW - Observers

KW - Nonlinear dynamical systems

KW - Nonlinear equations

KW - Robustness

KW - State estimation

U2 - 10.1109/CDC.2009.5399674

DO - 10.1109/CDC.2009.5399674

M3 - Conference contribution

SN - 9781424438716

SP - 6137

EP - 6142

BT - Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference

PB - IEEE

ER -

Nonlinear Observer Design for Discrete MIMO Systems with Unknown Time Delay

Abstract

Keywords

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