An extended prediction for uncertain LTI systems subject to input delays and unknown disturbances

Jin Zhang, Jing Shi and Chen Peng

Applied Mathematics and Computation, 2024, vol. 481, issue C

Abstract: This paper develops an extended prediction for uncertain linear time-invariant (LTI) systems with input delays and unknown disturbances. The developed prediction employs more information of the disturbances that allows to reject perfectly constant disturbances and to lead to better attenuation performance with smaller ultimate bounds for the time-varying disturbances. The assumption from the existing predictor-based work that the time-varying disturbances are smooth is not required. Moreover, we consider the system subject to uncertainties, i.e. the parameter uncertainties and the uncertain non-small delays, whose nominal values are assumed to be known. Compared to that for the uncertainty-free case, the resulting closed-loop system has additional errors due to the uncertainties. Then via Lyapunov-Krasovskii method, sufficient conditions are obtained in the form of linear matrix inequalities (LMIs) for finding the quantitative upper bounds on the uncertainties that guarantee the stability. We demonstrate that a better attenuation is achieved in the absence/presence of uncertainties. Finally, an example is presented to illustrate the efficiency of the method.

Keywords: Input delay; Disturbance attenuation; Predictive control; Uncertainties; LMIs (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300324003862
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:481:y:2024:i:c:s0096300324003862

DOI: 10.1016/j.amc.2024.128925

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().