Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
Perspectives of fuzzy systems and control
Fuzzy Sets and Systems
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
Parameterized linear matrix inequality techniques in fuzzy control system design
IEEE Transactions on Fuzzy Systems
On relaxed LMI-based designs for fuzzy regulators and fuzzy observers
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI
Automatica (Journal of IFAC)
Control synthesis of continuous-time T-S fuzzy systems with local nonlinear models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint
IEEE Transactions on Fuzzy Systems
Polynomial fuzzy models for nonlinear control: a Taylor series approach
IEEE Transactions on Fuzzy Systems
Switching fuzzy dynamic output feedback H∞ control for nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Guaranteed cost control analysis and iterative design for constrained Takagi-Sugeno systems
Engineering Applications of Artificial Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions
Fuzzy Sets and Systems
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Current fuzzy control research tries to obtain the less conservative conditions to prove stability and performance of fuzzy control systems. In many fuzzy models, membership functions with multiple arguments are defined as the product of simpler ones, where all possible combinations of such products conform a fuzzy partition. In particular, such situation arises with widely used fuzzy modelling techniques for nonlinear systems. These type of fuzzy models will be denoted as tensor-product (TP) fuzzy systems, because its expressions can be understood as operations on multi-dimensional arrays. This paper discusses the generalisation to TP fuzzy systems of the results in Kim and Lee [2000. New approaches to relaxed quadratic stability condition of fuzzy control systems. IEEE Transactions on Fuzzy Systems 2, 1571-1582] and Xiaodong and Qinling [2003. New approaches to H"~ controller designs based on fuzzy observers for T-S fuzzy systems via LMI. Automatica 39, 1571-1582]. The procedures here will allow to set up linear matrix inequality conditions which are less conservative than the cited ones, by exploiting the TP structure of the membership functions. A numerical example illustrates the achieved improvement.