Leith, Douglas J. and Leithead, W.E. (1998) Gain-Scheduled & Nonlinear Systems: Dynamic Analysis by Velocity-Based Linearisation Families. International Journal of Control, 70. pp. 289-317. ISSN 0020-7179
Download (330kB)
|
Abstract
A family of velocity-based linearisations is proposed for a nonlinear system. In contrast to the conventional series expansion linearisation, a member of the family of velocity-based linearisations is valid in the vicinity of any operating point, not just an equilibrium operating point. The velocity-based linearisations facilitate dynamic analysis far from the equilibrium operating points and enable the transient behaviour of the nonlinear system to be investigated. Using velocity-based linearisations, stability conditions are derived for both smooth and non-smooth nonlinear systems which avoid the restrictions, to trajectories lying within an unnecessarily, perhaps excessively, small neighbourhood about the equilibrium operating points, inherent in existing frozen-input theory. For systems where there is no restriction on the rate of variation, the velocity-based linearisation analysis is global in nature. The analysis techniques developed, whilst quite general, are motivated by the gain-scheduling design approach and have the potential for direct application to the analysis of gain-scheduled systems.
Item Type: | Article |
---|---|
Keywords: | Gain-Scheduled & Nonlinear Systems; Dynamic Analysis; Velocity-Based Linearisation Families; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 1840 |
Depositing User: | Hamilton Editor |
Date Deposited: | 12 Feb 2010 12:25 |
Journal or Publication Title: | International Journal of Control |
Publisher: | Taylor & Francis |
Refereed: | Yes |
URI: | |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only(login required)
Item control page |
Downloads
Downloads per month over past year