Interval type-2 fuzzy neural networkIn order to overcome the influence of model uncertainty and external disturbance on the trajectory tracking accuracy of four-wheel omnidirectional mobile robot (FM-OMR), a new adaptive trajectory tracking control scheme based on interval type 2 fuzzy neural network...
Ching-Hung, L., Chang, H., Ting Kuo, C., Chieh Chien, J., Wei Hu, T.: A Novel Recurrent Interval Type-2 Fuzzy neural Network for Nonlinear Channel Equilization. In: Proceeding of the Int. MultiConf. of Eng. and Computer Sci., pp. 7–12 (2009)...
Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, ...
Interval type-2 intuitionistic fuzzy setOnline learningTime series predictionThe prediction of time series has both the theoretical value and practical significance in reality. However, since the high nonlinear and noises in the time series, it is still an open problem to tackle with the ...
An interval type-2 fuzzy neural network (IT2FNN) control system is proposed for the precision control of a two-axis motion control system in this paper. The adopted two-axis motion control system is composed of two permanent-magnet linear synchronous motors. In the proposed IT2FNN control sys...
This paper proposes a self-adaptive interval type-2 neural fuzzy network (SAIT2NFN) control system for the high-precision motion control of permanent magnet linear synchronous motor (PMLSM) drives. The antecedent parts in the SAIT2NFN use interval type-2 fuzzy sets to handle uncertainties in PML...
In a type-2 fuzzy logic system, one of the important operations is to calculate the centroid of an interval type-2 fuzzy set (IT2 FS). In this paper, two novel algorithms called binary algorithms are proposed to calculate the centroid of IT2 FSs. Then, the outputs of the proposed binar...
Current studies of type-2 neural fuzzy systems (FSs) (NFSs) primarily focus on building a fuzzy model with high accuracy and disregard the interpretability of fuzzy rules. This paper proposes a data-driven interval type-2 (IT2) NFS with improved model interpretability (DIT2NFS-IP). The DIT...
Gain adaptive sliding mode controller based on interval type-II fuzzy neural network designed for attitude control for micro aircraft vehicle Purpose - Micro aerial vehicle is nonlinear plant; it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this pape....
In contrast with type-1 neural fuzzy systems (NFSs), interval type-2 NFSs process interval membership values are much more computationally expensive in implementation, especially for large-scale problems. Interval type-2 NFSs are conventionally implemented on a single-threaded central processing unit (...