An Interval Type-3 Fuzzy System and a New Online Fractional-Order Learning Algorithm: Theory and Practice

A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

“…The interval type-3 FLSs (IT3-FLSs) are developed to handle more level of uncertainties [37]. In this study, IT3-FLSs are used for online dynamic identification.…”

“…The main disadvantages of the above reviewed fuzzy based controllers for PV/battery system are that (1) simple FLSs are used to cope with uncertainties, (2) the effects of time-varying dynamics and radiations are not taken to account, (3) the stability and robustness of FLS based controller are not studied and (4) the learning algorithms with complicated structure and computational cost are used. Recently improved type-2 FLS (T2-FLS) and IT3-FLS have been presented [35]- [37]. It has been shown that improved FLSs result in higher performance in the wide engineering applications such as: model identification [38], fault detection problems [39], robotic systems [40], medical diagnosis systems [41], forecasting problems [42], control systems [38], classification problems [43], image processing [44], decision-making systems [45], and so on.…”

“…The interval type-3 membership function[37]. The closed-loop system is asymptotically stable if control signals and compensators are designed as(17)(18) and tuning rules for parameters of IT3-FLSs and estimated upper bound of approximation error (AE) are considered as…”

Exponential synchronization and stabilization of delayed feedback hyperchaotic financial system

“…Example 4.2 Consider the following data for systems (2.7), (2.9) and (2.10): Further computations give Remark 8 The dynamics are considered to be known for future direction. However, the authors in [27][28][29] proposed the potential estimation of uncertainties by the developed interval type-3 fuzzy systems and general type-2 fuzzy systems. In our next paper, similar considerations may be placed in the chaotic financial system, which is an interesting thing.…”

Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature

“…T3-FLSs are the generalization of T2-FLSs. The main idea for T3-FLS is presented in Reference [37], which was developed in this study for dynamic identification of a practical system. The basic superiority of T3-FLSs with respect to T2-FLSs is that, in type-3 membership functions (MFs), the upper and lower of uncertainties are considered to be fuzzy set, while, in the type-2 MFs, the upper and lower of uncertainties are considered to be crisp values.…”