Fuzzy systems can provide us with universal approximation models of deterministic input–output relationships, but in the stochastic environment few achievements related to the subject have so far achieved. In the paper a novel stochastic Takagi–Sugeno (T–S) fuzzy system is introduced to represent approximately existing randomness in many real-world systems. By recapitulating the general archite...

There are many papers in the literature that deal with the problem of the design of a fuzzy system from a set of given training examples. Those who get the best approximation accuracy are based on TSK fuzzy rules, which have the problem of not being as interpretable as Mamdany-type Fuzzy Systems. A question now is posed: How can the interpretability of the generated fuzzy rule-table base be inc...

This study introduces a mixed 2 fuzzy output feedback control design method for nonlinear systems with guaranteed control performance. First, the Takagi and Sugeno fuzzy model is employed to approximate a nonlinear system. Next, based on the fuzzy model, a fuzzy observer-based mixed 2 controller is developed to achieve the suboptimal 2 control performance with a desired disturbance rejection co...

When a class of fuzzy value functions constitute a metric space, the completeness and separability is an important problem that must be considered to discuss the approximation of fuzzy systems. In this paper, Firstly, a new tK-integral norm is defined by introducing two induced operators, and prove that the class of tK-integrable fuzzy value functions is a metric space. And then, the integral t...

There are many papers in the literature that deal with the problem of the design of a fuzzy system from a set of given training examples. Those who get the best approximation accuracy are based on TSK fuzzy rules, which have the problem of not being as interpretable as Mamdany-type Fuzzy Systems. A question now is posed: How can the interpretability of the generated fuzzy rule-table base be inc...