Generalization of stability criterion for Takagi--Sugeno continuous fuzzy model
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Stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model
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Robust fuzzy logic control of mechanical systems
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Improved H∞ control of discrete-time fuzzy systems: a cone complementarity linearization approach
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Stability analysis of the simplest Takagi-Sugeno fuzzy control system using circle criterion
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Reformulation of LMI-based stabilisation conditions for non-linear systems in Takagi-Sugeno's form
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Control law proposition for the stabilization of discrete Takagi-Sugeno models
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Further studies on stabilization conditions for discrete-time Takagi-Sugeno fuzzy systems
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IEEE Transactions on Fuzzy Systems
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Adaptive observers for TS fuzzy systems with unknown polynomial inputs
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Generalized nonquadratic stability of continuous-time Takagi-Sugeno models
IEEE Transactions on Fuzzy Systems
H∞ and mixed H2/H∞ control of discrete-time T--S fuzzy systems with local nonlinear models
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Presents an approach to stability analysis of fuzzy systems. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The approach exploits the gain-scheduling nature of fuzzy systems and results in stability conditions that can be verified via convex optimization over linear matrix inequalities. Examples demonstrate the many improvements over analysis based on a single quadratic Lyapunov function. Special attention is given to the computational aspects of the approach and several methods to improve the computational efficiency are described