This paper presents some theoretical considerations about the variance of a fuzzy set and introduces covering–based algorithm for computing bounds an interval Type–2 set. The proposed obtains all possible variances unlike other algorithms which are based on center centroid to obtain relative is proven be always bigger than absolute variance. A comparison given through different examples where s...

This work investigates the self-triggered control issue for interval type-2 (IT2) fuzzy systems. The transmission of system state is determined via a scheme. Instead continuously monitoring prespecified triggering condition, scheme can calculate next instant by latest triggered information. Then, means state, IT2 controller designed, whose rules and membership functions (MFs) be flexibly select...

In this paper, we present a general framework for the study of interval type-2 rough fuzzy sets by using both constructive and axiomatic approaches. First, several concepts and properties of interval type-2 fuzzy sets are introduced. Then, a pair of lower and upper interval type-2 rough fuzzy approximation operators with respect to a crisp binary relation is proposed. Classical representations ...

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure system performance under effect of behaviors, may become bigger even beyond capacity applications. Therefore, actuator saturation problem also must The type-2 Takagi-Sugeno (T-S) fuzzy model can describe parameter uncertainties more completely than type-1 T-S for a class n...

In this state-of-the-art paper, important advances that have been made during the past five years for both general and interval type-2 fuzzy sets and systems are described. Interest in type-2 subjects is worldwide and touches on a broad range of applications and many interesting theoretical topics. The main focus of this paper is on the theoretical topics, with descriptions of what they are, wh...

Type-2 fuzzy sets are growing in popularity as, for certain applications they model uncertainty and imprecision better than type1 fuzzy sets. However, type-2 fuzzy sets can be difficult to understand and explain. Recent work has introduced embedded type-2 fuzzy sets and the Representation Theorem which enable us to discuss type-2 fuzzy sets in a different way. In particular they allow for alter...

This article focuses on expanding the estimation of domain attraction (DOA) for discrete-time positive nonlinear systems subject to input saturation and parameter uncertainties. To facilitate analysis design, interval type-2 (IT2) polynomial fuzzy model is used represent plant capture Combining with IT2 controller, fuzzy-model-based (PIT2PFMB) control system formed analysis. enlarge DOA PIT2PFM...

We propose the design of an analog Interval Type-2 (IT2) fuzzy logic controller chip that is based on the realization approach of averaging of two Type-1 Fuzzy Logic Systems (T1 FLSs). The fuzzifier is realized using transconductance mode membership function generator circuits. The membership functions are made tunable by setting some reference voltages on the IC pins. The inference is realized...

This paper presents an implementation of a new robust control strategy based on interval type-2 fuzzy logic controller (IT2-FLC) applied to the wind energy conversion system (WECS). The generator used was variable speed turbine doubly fed induction (DFIG). Fuzzy concepts have been with great success in many applications worldwide. So far, vast majority systems type-1 controllers. However, T1-FL...