A course in fuzzy systems and control
A course in fuzzy systems and control
Automatica (Journal of IFAC)
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
H∞ fuzzy filtering of nonlinear systems with intermittent measurements
IEEE Transactions on Fuzzy Systems
Robust output regulation of T-S fuzzy systems with multiple time-varying state and input delays
IEEE Transactions on Fuzzy Systems
Stability analysis of fuzzy control systems subject to uncertain grades of membership
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On stability of fuzzy systems expressed by fuzzy rules with singleton consequents
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
IEEE Transactions on Fuzzy Systems
Analysis and design of an affine fuzzy system via bilinear matrix inequality
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
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We study the design of a state feedback controller for a class of nonlinear systems described by continuous-time affine fuzzy models. By introducing extra slack variables, the Lyapunov matrix and the system matrix are decoupled such that the controller parametrization is independent of the Lyapunov matrix. A novel quadratic stability analysis condition for affine fuzzy systems is derived in the formulation of linear matrix inequalities (LMIs), which is equivalent to existing results. Using the analytical results and a diffeomorphic state transformation, a stabilizing condition under which the affine fuzzy system is quadratically stabilizable is derived and can be solved by means of an LMI technique in conjunction with a search for scaling parameters. In contrast to existing work, the stabilizability condition we derive leads to less conservative LMI characterizations. The result is also extended to H"~ state feedback synthesis. Finally, a numerical example illustrates the merits of the new results.