This paper addressed the robust stabilization performance of Takagi–Sugeno (T-S) fuzzy systems under a state feedback controller. To attain this, an integral inequality is proposed by rearranging quadratic matrix-vector form combined with Jensen’s to handle single terms obtained taking derivative concerned Lyapunov–Krasovskii functional. By employing this and using techniques, some improved del...

today air conditioning systems have been considered by all people as one of welfarerequirements in buildings and closed environments. since a considerable part of energy lossoccurs in ordinary modern systems, new strategies and solutions are developed in the field inorder to save amount of energy consumption and observe environmental considerations. fuzzycontrol is one of these methods which pr...

Atanassov K. , Intuitionistic Fuzzy Sets. , VII ITKR's Section, Sofia, June 1983. Hashimoto H. , Sub-inverses of fuzzy Matrices, Fuzzy Sets and Systems, Vol. 12(1984),155-168. Murugadas P and Lalitha K. , Dual Implication Operator in Intuitionistic Fuzzy Matrices, International conference on Mathematical Modelling and its Application-2012. Sriram S and Murugadas P. , Sub-inverses of Intuit...

This paper deals with the stability issues of fuzzy control systems in the framework of T-S fuzzy models and the parallel distributed compensation. A hyperellipsoid-based approach is proposed for the stability analysis and synthesis of T-S fuzzy models. The minimal hyperellipoids are constructed by employing the support information in the fuzzy rules. Then, the stability conditions for open-loo...

Aneural-learning fuzzy technique is proposed for T–S fuzzy-model identification ofmodel-free physical systems. Further, an algorithm with a defined modelling index is proposed to integrate and to guarantee that the proposed neural-based optimal fuzzy controller can stabilize physical systems; the modelling index is defined to denote the modelling-error evolution, and to ensure that the training...

This paper presents the fuzzy-model-based control approach to synchronize two chaotic systems subject to parameter uncertainties. A fuzzy state-feedback controller using the system state of response chaotic system and the time-delayed system state of drive chaotic system is employed to realize the synchronization. The time delay which complicates the system dynamics makes the analysis difficult...