Results 121 to 130 of about 24,932,877 (195)

Multivariant Active Systems

Automation and Remote Control, 2001
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Avdeev, V. P., Kiseleva, T. V., Burkov, V. N.   +2 more
openaire   +1 more source

Adaptive control of linear multivariable systems using dynamic regressor extension and mixing estimators: Removing the high-frequency gain assumptions

at - Automatisierungstechnik, 2019
In this paper it is shown that, using the recently introduced dynamic regressor extension and mixing parameter estimation technique, it is possible to remove the key assumption of prior knowledge on the high frequency gain imposed in model reference ...
R. Ortega, D. Gerasimov, N. Barabanov, V. Nikiforov   +3 more
semanticscholar   +1 more source

Fuzzy Adaptive State-Feedback Control Scheme of Uncertain Nonlinear Multivariable Systems

IEEE transactions on fuzzy systems, 2019
In this article, we propose a new fuzzy adaptive state-feedback control strategy for unknown nonlinear multivariable systems whose the input-gains matrix is not necessarily symmetric and is characterized by nonzero leading principle minors.
A. Boulkroune, Loubna Merazka, Hongyi Li
semanticscholar   +1 more source

Adaptive unit vector control of multivariable systems using monitoring functions

International Journal of Robust and Nonlinear Control, 2018
An adaptive sliding‐mode unit vector control approach based on monitoring functions to deal with disturbances of unknown bounds is proposed. An uncertain multivariable linear system is considered with a quite general class of nonsmooth disturbances ...
L. Hsu, T. R. Oliveira, J. Cunha, Lin Yan   +3 more
semanticscholar   +1 more source

Building Multivariate Systems Biology Models

Analytical Chemistry, 2012
Systems biology methods using large-scale "omics" data sets face unique challenges: integrating and analyzing near limitless data space, while recognizing and removing systematic variation or noise. Herein we propose a complementary multivariate analysis workflow to both integrate "omics" data from disparate sources and analyze the results for specific
Kirwan, G.M., Johansson, E., Kleemann, R., Verheij, E.R., Wheelock, A.M., Goto, S., Trygg, J., Wheelock, C.E.   +7 more
openaire   +4 more sources

MvTools: Multivariable Systems Toolbox

CACSD. Conference Proceedings. IEEE International Symposium on Computer-Aided Control System Design (Cat. No.00TH8537), 2002
MvTools, (Multivariable Tools) is a toolbox for Matlab 5.3 developed within the Department of Electrical Systems and Automation (DSEA), University of Pisa, with the aim to offering to the Matlab users (especially control engineers and control engineering students) a complete toolbox for linear systems analysis and robust control synthesis.
CAMPA G, INNOCENTI, MARIO, DAVINI M.
openaire   +2 more sources

Multivariable System Regulation

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2006
The regulation of multivariable systems which are subjected to input set point changes and disturbances is considered. A regulation strategy, for analysis purposes, employing both an inner- and an outer-loop feedback structure is proposed. Prescribed, closed-loop, dynamic behaviour using minimum control effort while confining steady-state output ...
R Whalley, M Ebrahimi
openaire   +1 more source

Performance Recovery of Dynamic Feedback-Linearization Methods for Multivariable Nonlinear Systems

IEEE Transactions on Automatic Control, 2020
We show, in this paper, how a classical method for feedback linearization of a multivariable invertible nonlinear system, via dynamic extension and state feedback, can be robustified.
Yuanqing Wu, A. Isidori, Renquan Lu, H. Khalil   +3 more
semanticscholar   +1 more source

An Optimal Multivariable Control Strategy for Inductive Power Transfer Systems to Improve Efficiency

IEEE transactions on power electronics, 2020
Efficiency of wireless power transfer systems, based on inductive power transfer (IPT) technology, suffers significantly due to coil misalignment and load variations.
Yeran Liu, U. Madawala, R. Mai, Zhengyou He   +3 more
semanticscholar   +1 more source

Designing Robust Control for Mechanical Systems: Constraint Following and Multivariable Optimization

IEEE Transactions on Industrial Informatics, 2020
This article proposes a novel robust control design for mechanical systems based on constraint following and multivariable optimization. The state of the concerned system is affected by (possibly fast) time-varying and bounded uncertainty.
Qinqin Sun, Guolai Yang, Xiuye Wang, Ye-hwa Chen   +3 more
semanticscholar   +1 more source