THE PURPOSE. Development and analysis of control systems for cargo movement mechanisms that do not contain a speed sensor in their structure. The use intelligent devices the implementation sensorless systems. study proposed solutions closed-type order to identify most optimal option provides best performance according criteria, this case, accuracy testing. METHODS. It is possible achieve these ...

This paper proposes a practical solution to address the energy management issue in fuel cell hybrid electric vehicles (FCHEVs). revolves around powertrain system that contains (FC) as main supply, photovoltaic (PC) secondary source, and battery bank (Batt) backup storage compensate for FC’s low response rate. The this alternated between designated elements load via DC bus, maintain stable outpu...

In this paper, an optimal artificial neural network (ANN) controller for load frequency control (LFC) of a four-area interconnected power system with non-linearity is presented. A feed forward multi-layers and Bayesian regularization backpropagation (BRB) training function used. This designed on the basis theory to overcome problem as changes in system. The comprised transfer models twothermal ...

Abstract—This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMAL2...

In this work, a novel realization of the well known machine learning approach—reservoir computing (RC) using nanoelectromechanical system (NEMS) GaAs resonator is proposed. The specially designed can interact with laser directly without cavity. Thanks to richness nonlinearity embedded in light-mediated dynamical interacting process, RC platform performs outstandingly even by eliminating time de...

The development of a Time series Forecasting System is major concern for Artificial Intelligence researchers. Commonly, existing systems only assess temporal features and analyze the behavior data over time, thus, resulting in uncertain forecasting accuracy. Although many were proposed literature; they have not yet answered attending question. Hence, to overcome this problematic, we propose an ...

The prediction of chaotic time series with neural networks is a traditional practical problem of dynamic systems. This paper is not intended for proposing a new model or a new methodology, but to study carefully and thoroughly several aspects of a model on which there are no enough communicated experimental data, as well as to derive conclusions that would be of interest. The recurrent neural n...

In Part II of this paper, the identification and control problems of a nonlinear dynamical system are considered in a simplified framework. First it is shown that when the linearized system is observable, the state vector of the nonlinear system can be reconstructed from the input and the output together with their past values. This establishes the existence of solutions to regulation problems ...

In this paper, the voltage and frequency control of an isolated self-excited induction generator, driven by wind turbine, is developed with emphasis on nonlinear auto regressive moving average (NARMAL2) based on neural networks approach. This has the advantage of maintaining constant terminal voltage and frequency irrespective of wind speed and load variations. Two NARMA L2 controllers are used...

– This paper presents the optimization of a photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT). The optimization is suspended to reference optimal power. This optimization technique is developed to assure the optimum chopping ratio of buck-boost converter. The presented MPPT technique is used in photovoltaic water pumping system in order to optimize its e...