Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Control law proposition for the stabilization of discrete Takagi-Sugeno models
IEEE Transactions on Fuzzy Systems
A new fuzzy Lyapunov function approach for a Takagi--Sugeno fuzzy control system design
Fuzzy Sets and Systems
Perspectives of fuzzy systems and control
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Piecewise quadratic stability of fuzzy systems
IEEE Transactions on Fuzzy Systems
Parameterized linear matrix inequality techniques in fuzzy control system design
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Stability analysis of discrete-time fuzzy dynamic systems based on piecewise Lyapunov functions
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Generalized nonquadratic stability of continuous-time Takagi-Sugeno models
IEEE Transactions on Fuzzy Systems
Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions
Fuzzy Sets and Systems
Non-quadratic local stabilization for continuous-time Takagi--Sugeno models
Fuzzy Sets and Systems
Reduced-order dynamic output feedback control of continuous-time T--S fuzzy systems
Fuzzy Sets and Systems
Information Sciences: an International Journal
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The results offered in this paper constitute a way to overcome infeasible global quadratic conditions for stability of continuous-time Takagi-Sugeno (TS) models. It is shown that reducing global stability goals to something less restrictive will give a nice solution by providing an estimation of the stability domain (local asymptotic conditions), as it is usually the case for nonlinear models for which stability and/or stabilization cannot be reached globally. Conditions under the novel approach can be expressed as linear matrix inequalities (LMIs) which are efficiently solved by convex optimization techniques. Some examples are provided to illustrate how the proposed technique actually broadens stability analysis by leaving the quadratic framework.