This paper proposes two novel Kalman-based learning algorithms for an online Takagi-
Sugeno (TS) fuzzy model identification. The proposed approaches are designed based on …

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease
(PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference …

Fuzzy inference systems (FISs) are a predictive modeling technique based on fuzzy sets that
utilize approximate reasoning to mimic the decision-making process of human experts …

The fuzzy membership function is a crucial factor that may affect the model structure and
modeling accuracy. Although hyperplane-shaped clustering (HPSC) has been widely used …

Hyper-plane-shaped clustering (HPSC) has been proved to be more effective in Takagi–
Sugeno (T–S) fuzzy model identification compared with hyper-sphere-shaped clustering …

This paper is concerned with identifying a Takagi-Sugeno (TS) fuzzy model for turbofan aero-
engines working under the maximum power status (non-afterburning). To establish the fuzzy …

An evolving encoding scheme is presented in this article for a fuzzy-based nonlinear system
identification scheme, using the subtractive fuzzy C-mean clustering and a modified version …

The optimal number and location of control devices not only play a major role in an effective
structural control system but also lead to a cost-effective design. This article presents a multi …

This article studies the practical stability (PS) and finite-time stability (FTS) for fuzzy
descriptor systems with uncertainties of unknown bound. For such nonlinear descriptor …

For nonlinear descriptor systems, this paper presents an approach to obtain a fuzzy
controller with guaranteed finite-time stability and finite-time boundedness with non-zero …