a Mamdani interval type-2 FLS it may take less time to train an interval type-2 FLS to achieve a satisfactory performance, and the resulting system is more robust to noise. I. INTRODUCTION The knowledge used to construct a fuzzy logic system ...
The IT2 SFLS has the potential to outperform the singleton type-1 fuzzy logic systems (T1 SFLS). The IT2 SFLS systems accounts for the uncertainties that can be added during the system modeling and construction: the uncertain rules created using noisy data. There is no way to take into ...
type-reduction (TRdecomposed type-2 fuzzyThis article introduces the idea of decomposition of interval Type-2 fuzzy logic system into two parallel type-1 fuzzy systems. This decomposition avoids the problems associated with type-reduction techniques normally needed in type-2 fuzzy systems. Next, we...
Index Terms—Interval type-2 fuzzy sets, nonsingleton fuzzy logic systems, time-series forecasting, tuning of parameters, type-2 fuzzy logic systems, upper and lower membership functions. I. INTRODUCTION FUZZY logic system (FLS) (also known as a fuzzy system, fuzzy logic controller, etc) ...
Baklouti N, John R, Alimi AM (2012) Interval type-2 fuzzy logic control of mobile robots. J Intel Learn Syst Appl 4:291-302Alimi, Type-2 Fuzzy Logic Control of Mobile Robots - Baklouti, M - 2012 () Citation Context ...pdate using a fuzzy logic system. The big difference between...
Multi-class classification of motor imagery EEG signal.Adaptive neural fuzzy inference system (ANFIS) using one-vs-one and one-vs-all methods.Proposed an interval type-2 fuzzy fusion with ANFIS to improve uncertainty handling.Experimented on an online control task of moving a robot towards a ...
As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorit...
The proposed controller is designed by combining an adaptive Mamdani linguistic based interval type-2 fuzzy logic system (IT2-FLS) with sliding mode control technique. For the sake of the FAHV longitudinal model stably controlled under parametric and structural uncertainties which mainly come from ...
Type-1 fuzzy logic controller (T1FLC) has been proposed in13 as main LFC for two-area power system integrating solar park power plant and reduction oxidation flow battery (RFB) as fast active power source during disturbance, the proposed controller has achiever better performance compared to PID...
As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorit...