In this paper, we propose a method to judge the degree of the relationship closeness
between system input variables and theoretical output through independence test, and …

The observer-based output feedback control problem for nonlinear systems is studied
through Takagi–Sugeno fuzzy affine models. A novel piecewise fuzzy affine observer is …

Type-2 fuzzy neural networks (T2FNNs) have gained popularity due to their processing
ability for high uncertainty. However, concerned with the high-dimensional problems of …

Fuzzy neural network (FNN) is a structured learning technique that has been successfully
adopted in nonlinear system modeling. However, since there exist uncertain external …

In this study, an observer-based model predictive control (MPC) algorithm is addressed for
an uncertain discrete-time nonlinear networked control system (NCS) subject to hybrid …

Forecasting data is still an extensively investigated area of research specially in stock
markets. The subjectivity of the elements that influence the market oscillation is the main …

This study introduces a general type-2 Takagi–Sugeno–Kang fuzzy controller (GT2-TSKFC)
for controlling uncertain systems. The proposed GT2-TSKFC uses equidistant type-2 …

Control precision and robustness can be regarded as essential challenges of slip ratio
control because of the external uncertainties of road conditions and the internal delay …

Nonlinear systems, such as robotic systems, play an increasingly important role in our
modern daily life and have become more dominant in many industries; however, robotic …

Forecasting data is still an extensively investigated area of research specially in stock
markets. The subjectivity of the elements that influence the market oscillation is the main …