Perspectives of fuzzy systems and control

By Antonio Sala, Thierry-Marie Guerra, Robert Babuška. Fuzzy Sets Syst., 2005

430 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/a243131996d1cd4a4ce24f466cb01d488d14f388

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Citations in the corpus

SOFMLS: Online Self-Organizing Fuzzy Modified Least-Squares Network (2009, background): “Over the past few years, the application of fuzzy neural networks for nonlinear system identiﬁcation has been a very active area [5], [11], [36].”
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems (2006, background): “In addition to the aforementioned challenges, the authors in [245] have also listed a number of open problems and perspec-”
A New Design of Delay-Dependent Robust ${\cal H}_{\bm \infty}$ Filtering for Discrete-Time T--S Fuzzy Systems With Time-Varying Delay (2009, background): “See the survey papers [11] and [12] and the references cited therein for the most recent advances on this topic.”
A survey on industrial applications of fuzzy control (2011, positive): “The main advantage of TP model transformation in modifying the given LPV models to varying convex combinations of LTI models is that the LMI-based control design frameworks can be applied immediately to the resulting affine models in order to get a tractable and improved performance of the FCSs.”
Fuzzy Control Systems: Past, Present and Future (2019, background): “Here, no attempt is made to comprehensively review the literature which includes several excellent books [14], [17]–[20] and thousands of technical articles, see for instance [5], [10], [12], [21]–[23] and references therein.”
An alternative to inverse dynamics joint torques estimation in human stance based on a Takagi–Sugeno unknown-inputs observer in the descriptor form (2008, background): “Of course, the same kind of results can be obtained by introducing, for example, a decay rate on the Lyapunov function or finding an upper bound of a quadratic criterion (see Tanaka and Wang 2001, Sala et al. 2005 and references therein).”
Fuzzy-Model-Based Reliable Static Output Feedback $\mathscr{H}_{\infty }$ Control of Nonlinear Hyperbolic PDE Systems (2016, methodology): “Now, by a local sector nonlinearity approach [2], the nonlinear PDE system in (67)–(69) can be expressed by the following T–S fuzzy PDE model with four rules: Plant Rule R: IF ζ1(x1) is about ξi , and ζ2(x1) is about ζi , THEN ∂x(s, t) ∂t = −v ∂x(s, t) ∂s + (Ai(s) + ΔAi(s, t))x(s, t)”