State observer for a class of nonlinear systems and its application

Xinkai Chen; Guisheng Zhai

State observer for a class of nonlinear systems and its application

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, we consider the state observer problem for a class of nonlinear systems which are usually encountered in the machine vision study. The formulation of the state observer is motivated by the sliding mode methods and adaptive control techniques. The proposed observer is applied to the identification problems of the motion parameters and space position of a moving object by using the perspective observation. Simulation results show the proposed observer is very effective.

Original language	English
Pages	88-93
Number of pages	6
Publication status	Published - 2002 Jan 1
Externally published	Yes
Event	Proceedings of the 2002 IEEE International Conference on Control Applications - Glasgow, United Kingdom Duration: 2002 Sep 18 → 2002 Sep 20

Conference

Conference	Proceedings of the 2002 IEEE International Conference on Control Applications
Country	United Kingdom
City	Glasgow
Period	02/9/18 → 02/9/20

ASJC Scopus subject areas

Control and Systems Engineering

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title = "State observer for a class of nonlinear systems and its application",

abstract = "In this paper, we consider the state observer problem for a class of nonlinear systems which are usually encountered in the machine vision study. The formulation of the state observer is motivated by the sliding mode methods and adaptive control techniques. The proposed observer is applied to the identification problems of the motion parameters and space position of a moving object by using the perspective observation. Simulation results show the proposed observer is very effective.",

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year = "2002",

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language = "English",

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AU - Zhai, Guisheng

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AB - In this paper, we consider the state observer problem for a class of nonlinear systems which are usually encountered in the machine vision study. The formulation of the state observer is motivated by the sliding mode methods and adaptive control techniques. The proposed observer is applied to the identification problems of the motion parameters and space position of a moving object by using the perspective observation. Simulation results show the proposed observer is very effective.

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