In the study, the authors are interested in investigating the stability analysis and state
estimation of Markov jump static neural networks subject to time delays by the feat of Bessel …

Abstract Auto-Regressive-Moving-Average with eXogenous input (ARMAX) models play an
important role in control engineering for describing practical systems. However, ARMAX …

In this paper, a novel approach is proposed for adjusting the position of a magnetic levitation
system using projection recurrent neural network-based adaptive backstepping control …

In this paper, an optimal Sliding-Mode Control (SMC) technique based on Projection
Recurrent Neural Network (PRNN) is proposed to solve the tracking consensus for the …

ARMAX models are widely used in control engineering for both system description and
control design. They can accurately describe a large class of real processes with relatively …

In this paper, the powerful issue of a non-full rank inverse model control investigation is
provided. It is broadly known, that the inverse-based methodology is associated with the full …

To assess the performance of a control loop based on the minimum variance (MV)
benchmark, we need to calculate MV lower bound (MVLB). Even though there is a plethora …

The Autoregressive Moving Average (ARMAX) model with exogenous input is a widely used
discrete time series model, but its special structure allows outliers of its process to affect …

A novel neural network algorithm for indirect measurement of the polished rod load of the
beam‐pumping unit is proposed. The dynamometer card is a two‐dimension graph of …

抄録 This paper gives mathematical expressions of three control specifications of an
extended generalized minimum variance control (GMVC). The specifications are (1) the …