Search results for "feedforward"
showing 8 items of 28 documents
Unknown order process emulation
2002
Approaches the emulation problem using feedforward neural networks of single input single output (SISO) processes, applying a backpropagation method with a higher convergence rate. In this kind of application, difficult problems appear when the system's order is a priori unknown. A search through the SISO processes space is proposed, aiming to find a favorable neural emulator over the training examples set.
Fundamental Analysis of Grid-Forming Converters Enhanced with Feedforward Controls
2022
The grid-forming control for power converters can be enhanced by proper feedforward terms included in the active power control loop. Two basic structures are identified, the feedforward angle and the feedforward frequency. The formal analysis of the transfer functions reveals a structural similarity. The two schemes exhibit however a fundamental difference in their transient capabilities. The grid-forming controls are characterized with the introduction of two specific factors, for the direct assessment of the inertia and the damping which can be provided by the grid-forming converter. The sensitivity analysis of the two feedforward schemes indicates that the enhancement of the transient pe…
Adaptive Feed-Forward Neural Network for Wind Power Delivery
2022
This paper describes a grid connected wind energy conversion system. The interconnecting filter is a simple inductor with a series resistor to minimize three-phase current Total Harmonic Distortion (THD). Using the Recursive Least Squares (RLS) Estimator, an online grid impedance technique is proposed in the stationary reference frame using the Recursive Least Squares (RLS) Estimator. An Adaptive Feedforward Neural (AFN) Controller has also been developed using the inverse of the system to improve the performance of the current Proportional-Integral controller under dynamical conditions and provide better DC link voltage stability. The neural network weights are computed in real-time using …
A Neuro-Genetic Approach to Real-Time Visual Grasp Synthesis
2007
Grasping is an essential prerequisite for an agent, either human or robotic, to manipulate various kinds of objects present in the world. It is a fact that we would like robots to have the same skills as we do. However, despite the construction of human-hand-like robotic effectors, much work is still to be done in order to give robots the capability to grasp and manipulate objects. The goal of this work is to automatically perform grasp synthesis of unknown planar objects. In other words, we must compute points on the object's boundary to be reached by the robotic fingers such that the resulting grasp, among infinite possibilities, optimizes some given criteria. The space of possible config…
Investigation of vehicle crash modeling techniques: theory and application
2013
Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…
Reproduction of kinematics of cars involved in crash events using nonlinear autoregressive models
2012
Vehicle crashworthiness can be assessed by the variety of methods - the most common and direct one is a vehicle crash test. Visual inspection and obtained measurements, such as car acceleration, are used to examine impact severity of an occupant and overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using a feedforward neural network to estimate the system by use of nonlinear autoregressive (NAR) models. Specifically, feasibility of applying neural networks with an NAR model to the analysis of experimental data is explored by application to measurements of a vehicle crash test. This mo…
Anomaly Detection and Classification of Household Electricity Data : A Time Window and Multilayer Hierarchical Network Approach
2022
With the increasing popularity of the smart grid, huge volumes of data are gathered from numerous sensors. How to classify, store, and analyze massive datasets to facilitate the development of the smart grid has recently attracted much attention. In particular, with the popularity of household smart meters and electricity monitoring sensors, a large amount of data can be obtained to analyze household electricity usage so as to better diagnose the leakage and theft behaviors, identify man-made tampering and data fraud, and detect powerline loss. In this paper, the time window method is first proposed to obtain the features and potential periodicity of household electricity data. Combining th…
Facilitadores y flujos de aprendizaje como agentes dinamizadores en la gestión del capital intelectual y la performance corporativa
2012
El propósito fundamental de esta investigación es explorar hasta qué punto los componentes del capital intelectual establecen relaciones con los facilitadores para la creación de conocimiento, también con los flujos de aprendizaje feedback y feedforward, y cómo pueden estos, a su vez, influir en la performance de la organización. Para la consecución de este objetivo hemos estructurado este trabajo en tres grandes bloques. El primero de ellos incluye los fundamentos teóricos y ofrece una revisión de la investigación previa y de los conceptos relevantes de este trabajo. Está estructurado en tres capítulos: en el primero se realiza una aproximación del capital intelectual en el marco de la Teo…