JOURNAL ARTICLE

Stability and robustness analysis of MIMO MRAC usingKp=L2D2S2factorization

Xue‐Jun Xie

Year: 2008 Journal:   International Journal of Systems Science Vol: 39 (3)Pages: 265-278   Publisher: Taylor & Francis

Abstract

Abstract For a class of MIMO systems with input and output unmodeled dynamics, bounded disturbances and any relative degree, using the idea of Kp = L 2 D 2 S 2 factorization, the design and analysis of robust direct model reference adaptive control are further investigated in this article. By establishing the Lp and L 2δ relationship properties between the input and output, multivariable swapping lemmas and relating all the signals in the closed-loop system with the normalizing signal, stability and robustness of adaptive system are analyzed rigorously. Compared with the existing results, the proof procedure is more compact and simple. A simulation example verifies the effectiveness of the control scheme. Keywords: MIMO systemsUnmodeled dynamics K p = L 2 D 2 S 2 factorizationMRAC Acknowledgments The authors would like to thank the reviewers for their comments and suggestions. This work is supported by Program for New Century Excellent Talents in Universities of China (NCET-05-0607), National Natural Science Foundation of China (60774010), and Project for Fundamental Research of Natural Sciences in Universities of Jiangsu Province (07KJB510114).

Keywords:
Robustness (evolution) Control theory (sociology) MIMO Mathematics Bounded function Factorization Multivariable calculus Computer science Algorithm Control (management) Mathematical analysis Engineering Control engineering Statistics

Metrics

9
Cited By
1.58
FWCI (Field Weighted Citation Impact)
20
Refs
0.86
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Stability and Control of Uncertain Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Control Systems Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering

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