Robustness design of nonlinear systems: fuzzy Lyapunov approach
AEE'08 Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering
Fuzzy hyperbolic neural network with time-varying delays
Fuzzy Sets and Systems
Fuzzy control of inverted pendulum and concept of stability using Java application
Mathematical and Computer Modelling: An International Journal
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We present a new approach to fuzzy modeling and control of discrete-time systems which is based on the formulation of a novel state-space representation using the hyperbolic tangent function. The new representation, designated the hyperbolic model, combines the advantages of fuzzy system theory and classical control theory. On the one hand, the hyperbolic model is easily derived from a set of Mamdani-type fuzzy rules. On the other hand, classical control theory can be applied to design controllers for the hyperbolic model that not only guarantee stability and robustness but are themselves equivalent to a set of Mamdani-type fuzzy rules. Thus, this new approach combines the best of two worlds. It enables linguistic interpretability of both the model and the controller, and guarantees closed-loop stability and robustness.