Search results for "vector"
showing 10 items of 2660 documents
A novel correction method for a low cost sensorless control system of IPMSM electrical drives
2008
In this paper a novel correction method for sensorless Field Oriented Control System of Brushless internal Permanent Magnet Electrical Drives is introduced discussed and experimentally validated. The novelty of this control system is the estimation of rotor speed and angular position is based on the back electromotive force space vector determination, without the aid of voltage probes. Actual voltage signals needed for estimation are replaced with the reference ones given by the current controller. This choice obviously introduces an error that have been vanished by means of a new compensating function or with the aid of data coming from experimental tests. Experimental verifications of the…
Experimental Implementation of an Enhanced Field Oriented Control Strategy for Induction Motors Using a Low-Cost ATSAM3X8E Microcontroller
2020
This paper presents a low-cost Micro Controller Unit (MCU) implementation of an enhanced Field Oriented Control (FOC) technique that takes into account the non-linearity of the ferromagnetic material. The algorithm is applied to a three-phase 5.5 kW Induction Motor (IM) and experimentally carried out by means of an ATMEL ATSAM3X8E microcontroller. The effectiveness of the enhanced control strategy is verified by comparing the dynamic performances of the electric drive with those obtained by means of a traditional FOC technique. For this purpose, an experimental test bench is set up for the implementation of the enhanced FOC technique. Finally, the technical and economic features of the simp…
Aspects Concerning SVM Method’s Scalability
2008
In the last years the quantity of text documents is increasing continually and automatic document classification is an important challenge. In the text document classification the training step is essential in obtaining a good classifier. The quality of learning depends on the dimension of the training data. When working with huge learning data sets, problems regarding the training time that increases exponentially are occurring. In this paper we are presenting a method that allows working with huge data sets into the training step without increasing exponentially the training time and without significantly decreasing the classification accuracy.
Monitoring fire-affected areas using Thematic Mapper data
2001
In this paper three methods for updating inventories of burned areas have been presented and examined. They include Multitemporal Principal Component Analysis (MPCA), Change Vector Analysis (CVA) a...
Global RDF Vector Space Embeddings
2017
Vector space embeddings have been shown to perform well when using RDF data in data mining and machine learning tasks. Existing approaches, such as RDF2Vec, use local information, i.e., they rely on local sequences generated for nodes in the RDF graph. For word embeddings, global techniques, such as GloVe, have been proposed as an alternative. In this paper, we show how the idea of global embeddings can be transferred to RDF embeddings, and show that the results are competitive with traditional local techniques like RDF2Vec.
Supervised learning of time-independent Hamiltonians for gate design
2018
We present a general framework to tackle the problem of finding time-independent dynamics generating target unitary evolutions. We show that this problem is equivalently stated as a set of conditions over the spectrum of the time-independent gate generator, thus transforming the task to an inverse eigenvalue problem. We illustrate our methodology by identifying suitable time-independent generators implementing Toffoli and Fredkin gates without the need for ancillae or effective evolutions. We show how the same conditions can be used to solve the problem numerically, via supervised learning techniques. In turn, this allows us to solve problems that are not amenable, in general, to direct ana…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions
2018
Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…
Comparative study of modelling the thermal efficiency of a novel straight through evacuated tube collector with MLR, SVR, BP and RBF methods
2021
Abstract Data-based methods are useful for accurate modelling of solar thermal systems. In this work, several artificial neural network (ANN) techniques are proposed to predict the thermal performance of an all-glass straight through evacuated tube solar collector. These are compared to support vector regression analysis. Extensive experimental data sets were collected for training the ANN models. Solar radiation intensity, ambient temperature, wind speed, mass flow rate and collector inlet temperature were selected as the input layer to predict the thermal efficiency of the solar collector. The prediction precision of the ANN models was compared to the multiple linear regression and suppor…
Relativistic kinematic approach to the classical ideal gas
2019
he necessary and sufficient conditions for a unit time-like vector field to be the unit velocity of a classical ideal gas are obtained. In a recent paper [Coll, Ferrando and S\'aez, Phys. Rev D {\bf 99} (2019)] we have offered a purely hydrodynamic description of a classical ideal gas. Here we take one more step in reducing the number of variables necessary to characterize these media by showing that a plainly kinematic description can be obtained. We apply the results to obtain test solutions to the hydrodynamic equation that model the evolution in local thermal equilibrium of a classical ideal gas. \end{abstract}