IEEE Transactions on Fuzzy Systems
Intermediate variable normalization for gradient descent learning for hierarchical fuzzy system
IEEE Transactions on Fuzzy Systems
Three-dimensional min--max-gravity based fuzzy PID inference analysis and tuning
Fuzzy Sets and Systems
Stability analysis of continuous-time recurrent fuzzy systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
International Journal of Applied Mathematics and Computer Science
A novel fuzzy framework for nonlinear system control
Fuzzy Sets and Systems
Exact inversion of decomposable interval type-2 fuzzy logic systems
International Journal of Approximate Reasoning
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This paper presents the decomposition property of fuzzy systems using a simple, constructive, decomposition procedure. That is, by properly dividing the input space into sub-input spaces, a general fuzzy system is decomposed into several sub-fuzzy systems which are the simplest fuzzy systems in the sub-input spaces. Based on the decomposition property of fuzzy systems, the analysis of fuzzy systems can be divided into two steps: first, analyze the properties of the simplest fuzzy systems, and then, use the decomposition property to extend the results to general fuzzy systems. Using this idea, two applications of the decomposition property are given. The first is the application to the representation capability analysis of fuzzy systems. The second is the application to the analysis of a class of nonlinear control systems. Then, based on the piecewise affine fuzzy-system model, the existence condition and the design of a stable control for a class of single-input single-output (SISO) nonlinear systems are presented