Intelligent digital redesign for non-linear systems: observer-based sampled-data fuzzy control approach

Geun Bum Koo; Jin Bae Park; Young Hoon Joo

Intelligent digital redesign for non-linear systems: observer-based sampled-data fuzzy control approach

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Author(s): Geun Bum Koo ¹ ; Jin Bae Park ¹ ; Young Hoon Joo ²
- Affiliations: 1: Department of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea ;
  2: Department of Control and Robotics, Kunsan National University, Kunsan, Chonbuk 573-701, Korea
Source: Volume 10, Issue 1, 04 January 2016, p. 1 – 9
DOI: 10.1049/iet-cta.2015.0244 , Print ISSN 1751-8644, Online ISSN 1751-8652

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Received 21/03/2015, Accepted 24/08/2015, Revised 13/07/2015, Published 04/01/2016

In this study, an intelligent digital redesign (IDR) technique is proposed for an observer-based sampled-data fuzzy controller of non-linear systems. By using a Takagi–Sugeno fuzzy model, the pre-designed analog and sampled-data fuzzy controllers are supposed, and these discretised closed-loop systems are obtained, respectively. Based on the IDR problem, the authors guarantee both stability and state-matching conditions. Unlike the previous techniques, the proposed IDR not only improves the state-matching performance using the state-matching error cost function, but is also derived in the strict linear matrix inequality format. In a numerical example, the effectiveness of the proposed technique and the results of the improved performance are shown.

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Intelligent digital redesign for non-linear systems: observer-based sampled-data fuzzy control approach

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