NDLI: Takagi-Sugeno control of the elevation channel of a twin-rotor system using closed-loop empirical data

Content Provider	IEEE Xplore Digital Library
Author	Azimian, H. Fatehi, A. Araabi, B.N.
Copyright Year	2012
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Univ. of Tehran, Tehran, Iran (Araabi, B.N.) \|\| Adv. Process Autom. & Control (APAC) Res. Group, K. N. Toosi Univ. of Technol., Tehran, Iran (Fatehi, A.) \|\| Dept. of Mech. & Mater. Eng., Univ. of Western Ontario (UWO), London, ON, Canada (Azimian, H.)
Abstract	In this paper, design of Takagi-Sugeno controllers for a twin-rotor system from empirical data is addressed. First, identification of linear models using Prediction Error Method in the presence of nonlinear distortions and in feedback systems is revisited, and it is demonstrated that feedback nonlinear systems with an integral action can be locally represented by linear models rather than affine models. Moreover, it is demonstrated that how the consistency and unbiasedness of the identified models can be improved by proper design of the experiments. In order to ensure that the unmodeled contributions in the resulting piecewise linear model are sufficiently small, a criterion is proposed based on the small-gain theorem that can be used for unfalsification of the piecewise linear model. Finally, by taking advantage of the separation principle, design of fuzzy Takag-Sugeno state feedback and observer is formulated in terms of Linear Matrix Inequalities (LMIs). The implementation results on the actual system demonstrate significant improvements with respect to the initial controller and previous work on similar systems.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	2615
Ending Page	2620
File Size	1981038
Page Count	6
File Format	PDF
ISBN	9781457710957
ISSN	07431619
e-ISBN	9781457710964
e-ISBN	9781467321020
DOI	10.1109/ACC.2012.6315695
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Nonlinear systems Closed loop systems Observers Uncertainty Data models Predictive models
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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