In this paper, we present the interval neutrosophic logics which generalizes the fuzzy logic, paraconsistent logic, intuitionistic fuzzy logic and many other non-classical and non-standard logics. We will give the formal definition of interval neutrosophic propositional calculus and interval neutrosophic predicate calculus. Then we give one application of interval neutrosophic logics to do appr...

Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design p...

Abstract: In this paper, a new hierarchical data-driven modelling strategy based on Interval Type-2 Fuzzy Clustering is elicited for the Interval Type-2 Takagi-Sugeno-Kang (TSK) Fuzzy Logic System. This framework which we have called the IT2-Squared framework uses interval type-2 fuzzy clustering for initial antecedent parameters and structures determination and least-squares algorithm for deri...

Nonlinear inter-symbol interference leads to significant error rate in nonlinear communication and digital storage channel. In this paper, therefore, a novel recurrent interval type-2 fuzzy neural network with asymmetric membership functions (RT2FNN-A) is proposed for nonlinear channel equalization. The RT2FNN-A uses the interval asymmetric type-2 fuzzy sets and it implements the fuzzy logic sy...

Controller design remains an elusive and challenging problem for uncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) in comparison with type-1 fuzzy logic systems claim to effectively handle system uncertainties especially in the presence of disturbances and noises, but lack a formal mechanism to guarantee performance. In contrast, adaptive sliding mode control (ASMC) pro...

A novel adaptive fuzzy logic controller (AFC) based on interval type-2 fuzzy is proposed for vehicle non-linear active suspension systems. The adaptive strategy elicited from Least Means Squares optimal algorithm (LMS) is adopted to self-tune lower bounds and upper bounds of interval type-2 fuzzy membership functions (IMFs). The IMFs are utilized in the AFC design to deal with not only non-line...

Type-2 fuzzy logic systems are an area of growing interest over the last years. The ability to model uncertainties and to perform under noisy conditions in a better way than type-1 fuzzy logic systems increases their applicability. A new stable on-line learning algorithm for interval type-2 Takagi–Sugeno–Kang (TSK) fuzzy neural networks is proposed in this paper. Differently from the other rece...