<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Tracking controller design for a class of nonminimum-phase systems via the method of system center

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2001Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Automatic Control, volume 46, pages 1,639-1,643 (issn: 0018-9286,

Authors: I.A. Shkolnikov; Yuri B. Shtessel;

doi: 10.1109/9.956064

Tracking controller design for a class of nonminimum-phase systems via the method of system center

- Summary
- Subjects
- Related research
  (1)
- Metrics

Abstract

The paper presents a method of approximate output tracking for a class of causal nonminimum-phase multiple-input-multiple-output (MIMO) systems with nonlinear time-varying uncertainties and unmeasurable disturbances. The nonminimum-phase output-tracking problem is transformed into a state-tracking problem. The techniques used in the paper are based on the internal model principle and some algebraic methods. The developed design technique is illustrated by an example. The sliding mode control approach used in the example gives a completely constructive algorithm. The paper is a direct extension of \textit{Yu. B. Shtessel} [IEEE Trans. Autom. Control 42, 1282-1286 (1997; Zbl 0900.93052)] to the nonminimum-phase case.

Related Organizations

Alabama Agricultural and Mechanical University
United States
University of Alabama in Huntsville
United States

Keywords

nonminimum phase tracking, Design techniques (robust design, computer-aided design, etc.), Nonlinear systems in control theory, servocompensators, causal uncertain nonlinear systems, internal model principle

1 Research products, page 1 of 1

Non-Causal State Estimation for Improved State Tracking in Iterative Learning Control
2022IsAmongTopNSimilarDocuments

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	32
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average