New approaches to relaxed quadratic stability condition of fuzzy control systems

By Euntai Kim, Heejin Lee. IEEE transactions on fuzzy systems, 2000

817 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/f0256663544e1f5d0df63de85b28cf9a6887423d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computational Theory and Mathematics

In Mechanics of Materials

Citations in the corpus

On relaxed LMI-based designs for fuzzy regulators and fuzzy observers (2001, methodology): “where . Proof: See [ 12 ]. The following lemma will be useful in the proof of our relaxed conditions.”
A systematic approach to improve multiple Lyapunov function stability and stabilization conditions for fuzzy systems (2009, neutral): “Therefore much effort has been devoted to obtaining less conservative conditions based on the common quadratic Lyapunov function [10,11,18,20,24,34,38].”
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems (2006, background): “8), or to reduce its conservatism, or both [142], [192], [198], [267], [275], [286], [304].”
Stability and Stabilization of Delayed T--S Fuzzy Systems: A Delay Partitioning Approach (2009, background): “928598 mention a few, the problem of stability analysis is investigated in [19], [29], and [31]; stabilizing and H∞ control designs are reported in [4], [5], [15], [22], [28], [40], [45], and [47]; state estimation is addressed in [1], [10], and [46]; reliable control strategies are presented in [34”
Control Design for Interval Type-2 Fuzzy Systems Under Imperfect Premise Matching (2014, background): “More relaxed stability conditions under PDC can be found in [17]–[19].”
Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems (2008, background): “The importance of the membership function of the type-1 T-S fuzzy model to system stability was revealed in [4]–[6].”
A new fuzzy Lyapunov function approach for a Takagi-Sugeno fuzzy control system design (2006, methodology): “For the better relaxation, the other method in [8,17,19] can be applied as mentioned in Remark 4.”
New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI (2003, methodology): “Consider a continuous fuzzy plant composed of the following two rules: In Example 2 of Kim and Lee (2000), the region 2 6 b ¡ 9 : 75 ; 2 6 a 6 6 is the parameter region where the stability of the fuzzy control system is ensured by Theorem 1.”