The main aim of this paper is to establish a reliable model of a process behavior both for the steady-state and unsteady-state regimes. The use of this accurate model allows distinguishing a normal mode from an abnormal one. Therefore the neural black-box identification by means of a NARX (Nonlinear Auto-Regressive with eXogenous) model has been chosen. It shows the choice and the performance o...

Green methanol production, based on intermittent renewable energy sources, requires a more flexible operation mode and close integration with other sections, such as, the electrical grid electrolysis processes. In this study, synthesis distillation processes (MSD) for pilot-scale green production (corresponding to 22,236 tons/year) were investigated by dynamic modeling, focusing analysis charac...

This paper describes a multi-step algorithm used to predict and typify the energy consumption profile of prosumer, allowing automation design self-consumption photovoltaic (PV) power systems in novel platform called PV SPREAD. The uses different methodologies address various possible scenarios data availability. In this paper, those are addressed using nonlinear autoregressive artificial neural...

In this paper, we consider the nonlinear system modelling problem for on-chip testing and diagnosis of embedded mixed-signal systems. A SituationDependent AutoRegressive model with eXogenous variable (SDARX) is introduced to approximate the conventional Nonlinear-ARX (NARX). The parameter search space is divided into a linear weight subspace and the nonlinear parameter subspace. A nonlinear par...

The extreme values of high tides are generally caused by a combination astronomical and meteorological causes, as well the conformation sea basin. One place where tide have considerable practical interest is city Venice. MOSE (MOdulo Sperimentale Elettromeccanico) system was created to protect Venice from flooding highest tides. Proper operation protection requires an adequate forecast model ti...

October December 2016 2677 JCPS Volume 9 Issue 4 Inverse Kinematics Solution of a Five Joint Robot Using NARX Algorithm I. Jacob Raglend, M. Dev Anand, G. Glan Devadhas, D. M. Mary Synthia Regis Prabha Department of Electrical and Electronics Engineering, Noorul Islam Centre for Higher Education, Kumaracoil 629 180, Thuckalay, Kanyakumari District, Tamilnadu State, India Department of Mechanica...

An Artificial Neural Network (ANN), a Machine Learning (ML) modeling approach is proposed to predict the ecological state of North Lagoon Tunis, shallow restored Mediterranean coastal ecosystem. A Nonlinear Auto Regressive with exogenous input (NARX) neural network model was fitted Chlorophyll-a (Chl-a) concentrations in Tunis as an eutrophication indicator. The based on approximately three dec...

A novel biped walking pattern combining robust zero-moment-point ZMP technique and pre-determined foot-lifting value is proposed in this paper. The implementation of suggested approach contains following stages. Initially, a one-step curve for small-sized humanoid created using the 3rd-order interpolating equation, with velocity responding concept. next step, gait planning modeled as non-linear...

<p>Water quality plays a major role in issues related to public health and marine life. Hence, monitoring river for contaminations is vital ensuring safe sustainable water resources. Conventional method assessing index costly as it requires considerable amount of time laboratory Therefore, this study proposes model based on artificial neural network. A six-year data Air Busuk River obtain...