Affine TS-model-based fuzzy regulating/servo control design
Fuzzy Sets and Systems
Mixed H$_2$/H$_&infty;$ region-based fuzzy controller design for continuous-time fuzzy systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
LMI static output-feedback design of fuzzy power system stabilizers
Expert Systems with Applications: An International Journal
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Stability of cascaded fuzzy systems and observers
IEEE Transactions on Fuzzy Systems
State estimation of nonlinear systems using multiple model approach
ACC'09 Proceedings of the 2009 conference on American Control Conference
A neural-fuzzy sliding mode observer for robust fault diagnosis
ACC'09 Proceedings of the 2009 conference on American Control Conference
Adaptive observers for TS fuzzy systems with unknown polynomial inputs
Fuzzy Sets and Systems
Sequential stability analysis and observer design for distributed TS fuzzy systems
Fuzzy Sets and Systems
Dynamic output feedback controller for a harvested fish population system
CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals
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We focus on the analysis and design of two different sliding mode observers for dynamic Takagi-Sugeno (TS) fuzzy systems. A nonlinear system of this class is composed of multiple affine local linear models that are smoothly interpolated by weighting functions resulting from a fuzzy partitioning of the state space of a given nonlinear system subject to observation. The Takagi-Sugeno fuzzy system is then an accurate approximation of the original nonlinear system. Our approach to the analysis and design of observers for Takagi-Sugeno fuzzy systems is based on extending sliding mode observer schemes to the case of interpolated multiple local affine linear models. Thus, our main contribution is nonlinear observer analysis and design methods that can effectively deal with model/plant mismatches. Furthermore, we consider the difficult case when the weighting functions in the Takagi-Sugeno fuzzy system depend on the estimated state