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Navigation of mobile robots in dynamic and unknown environments is usually cluttered with noise and errors. In the literature, several solutions have been proposed. Recently, type-2 fuzzy logic have showed having the ability to handle uncertainties, imprecise and incomplete data. Since, it has been constituted a new hopeful and promising technique for further improve control of mobile robots in real...
The automated evolutionary design of an optimal hierarchical fuzzy system combined with the use of Interval Type-2 Fuzzy Systems and the Beta basis function is considered in this study. The resulted proposed system is named the Hierarchical interval Type-2 Beta Fuzzy System (HT2BFS). For the learning process, two main optimizations steps are considered. The first one executes the structure learning...
In this paper we introduce the Interval type-2 Beta fuzzy set as a membership function in a Fuzzy Logic System (FLS). First order derivatives of type-1 and type-2 Beta functions were developed for designing fuzzy logic systems based on given input-output pairs. Then, the steepest descent algorithm is used to train Beta fuzzy basis functions to obtain the final fuzzy system. The performance of the...
Human interact with natural language. Words are uncertain, vague and imprecise. Besides, words mean different things to different people. So, the use of numerical model to represent words is a difficult task. In this paper, we propose to give a new review of the most used computing with words methods especially encoding ones. Many approaches were used for computing with words. Some of these methods...
Recently, there has been a considerable interest on learning type-2 fuzy logic systems, essentially on how determining the footprint of uncertainties of linguistic variables. In fact, the complexity and difficulty in developing type-2 fuzzy systems can be located at the time of deciding which are the best parameters of membership functions (MFs). In real robot applications, the task of designing a...
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