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JRM Vol.28 No.5 pp. 745-751
doi: 10.20965/jrm.2016.p0745
(2016)

Paper:

FRIT of Internal Model Controllers for Poorly Damped Linear Time Invariant Systems: Kautz Expansion Approach

Hnin Si* and Osamu Kaneko**

*Graduate School of Natural Science and Technology, Kanazawa University
Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan

**Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

Received:
April 5, 2016
Accepted:
July 12, 2016
Published:
October 20, 2016
Keywords:
data-driven approach, fictitious reference iterative tuning (FRIT), internal model control (IMC), poorly damped systems, Kautz expansion
Abstract

FRIT of Internal Model Controllers for Poorly Damped Linear Time Invariant Systems: Kautz Expansion Approach

Data-driven approach to internal model controller with tunable parameters

This paper addresses the tuning of data-driven controllers for poorly damped linear time-invariant systems in the internal model control (IMC) architecture. In this study, fictitious reference iterative tuning (FRIT), which is one of the controller parameter tuning methods with the data obtained from a one-shot experiment, is used for tuning the controller. The Kautz expansion method in which the coefficients are tunable parameters is introduced to approximate the dynamics of linear time-invariant systems, which have poor damping characteristics. Such an approximated model with tunable parameters is implemented in the IMC architecture. A model and a controller can be realized simultaneously with a one-shot experiment by tuning the IMC with the parameterized Kautz expansion model and by using FRIT. The validity of the proposed method is examined with a numerical example.

Cite this article as:
H. Si and O. Kaneko, “FRIT of Internal Model Controllers for Poorly Damped Linear Time Invariant Systems: Kautz Expansion Approach,” J. Robot. Mechatron., Vol.28, No.5, pp. 745-751, 2016.
Data files:
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Last updated on Nov. 16, 2018