MIMO Feedback Error Learning without Recourse to Positive Realness —Improvement of Prefilter-Integration-type Learning Law

Makoto Noguchi; Kenji Sugimoto

doi:10.5687/iscie.24.61

Transactions of the Institute of Systems, Control and Information Engineers

Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668

Papers

MIMO Feedback Error Learning without Recourse to Positive Realness

—Improvement of Prefilter-Integration-type Learning Law

Makoto Noguchi, Kenji Sugimoto

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Keywords: Feedback Error Learning (FEL), strictly proper plant, multi-input multi-output, feedforward control

JOURNAL FREE ACCESS

2011 Volume 24 Issue 3 Pages 61-72

DOI https://doi.org/10.5687/iscie.24.61

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Abstract

This paper proposes an improved learning scheme for MIMO-FEL (Muliti-input multi-output feedback error learning) of prefilter-integration-type. Compared with an existing scheme, which is based on the gradient method and easily implemented, the proposed scheme does not require positive realness of the closed loop system. The paper shows the parameters converge to true values under a PE condition, and verifies its effectiveness in terms of simulation.

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