The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation...
In this manuscript, we investigate a collaborative filtering method to characterize consumption behavior (or evaluation) of customers (or users) and services (or items) for marketing. Assuming that each customer and service have the invisible attribute, which is called latent class, we propose a new Bayesian statistical model that consumption behavior is probabilistically arise based on a latent class...
Recently, in the field of building energy efficiency, many works focused on model based energy management services but developing models consistent with a measured reality is still an issue. Fine physical models with many parameters cannot be adjusted while non-physical models cannot extrapolate to situations never met in the training data. In this paper, pure data models will be implemented with...
Multiscale systems are characterized by dynamics that evolve over different times scales and are encountered frequently in process industries. Conventional identification techniques yield poor results when applied directly to MS systems because of their inherent assumption that the system evolves at a single scale. In this paper, we discuss the key challenges in the discrete-time (DT) identification...
Ocean wave energy farms are composed of several wave energy converter devices. The objective of each converter is to capture the potential and kinetic energy in rolling ocean waves and convert them into electricity. An important task in optimizing power delivery from ocean wave energy farms is short term prediction of incoming ocean waves. Accurate predictions enable predictive wave energy converter...
The generation model of speech signal has been regarded as an all-pole AR model. Distortion will happen when normal speech is disturbed or interfered. In this paper, we proposed a new signal model excited by the non-white noise signal to represent transfer function of a closed oxygen mask. Using LPC method to find the parameters of the all-pole signal model from the practical distortion signal, the...
Quadrotor is a highly non-linear system with complex dynamics. For a stable flight, it requires anefficient control scheme. This paper first present a discrete PD, PI and PID controllers based control scheme. It is a simple control strategy, capable of controlling the quadrotor. This paper also presents the non-linear model predictive control of quadrotor. Model predictive control is a digital control...
Traditional parameter estimation techniques deliver estimates for a given set of parameters, but do not in general provide an estimate of the parameter variability for systems with time-varying parameters. Accurate knowledge of the parameter variability becomes crucial in many contexts, e.g. robust control techniques. This paper proposes a method for joint parameter and variability estimation (PVE)...
In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results in relation to model order and the order which yields a sufficient level of accuracy is determined...
The present contribution addresses the problem of designing an adequate persistent excitation for state space identification of max-plus-linear systems. The persistent excitation is designed using the same techniques that have recently been developed for model predictive control for max-plus-linear systems. The application of this method for input signal design allows to incorporate additional objectives...
In social network analysis, retweet scale prediction is one important studying focus. Generally speaking, there are two different approaches to predict the retweet scale: time-series approach and non-time-series approach. In this paper, we conduct a research on the distribution of the reaction time in retweeting activity and introduce a time-series prediction model. We show that in retweeting activity,...
In multivariable control the study of loop interactions is of prime importance. The P or V-canonical form structures, where loop interactions are dealt with as feed-forward couplings, are popular transfer function representations used to describe multivariable processes. Another alternative design consists of a bank of several Single Input Single Output (SISO) controllers linked by feed-forward terms...
Reliability of any software product is a quantifiable attribute which is essential for predicting the degree of credibility of the software to operate accurately for a specific period of time without the occurrence of any kind of failure. Prediction of the behaviour of the software before its final shipment is an important task and behaviour includes satisfactory performance which is largely depends...
This paper investigates the Lithium-ion battery remaining useful life (RUL) prediction problem under grey model framework. The Lithium-ion battery capacity degradation is described with the help of grey model and revised grey model, respectively, and the least squares is employed to identify the unknown parameters in the grey models. Then the RUL prediction is presented based on the grey models. The...
The probabilistic characteristics of components can't be completely expressed by the S-N curve with parameters estimated by small number of specimens. Particle Swarm Optimization (PSO) is introduced to fit parameters with the incomplete test data, which can take advantage of the entire information of the specimens to obtain the globally optimal solution. With the fitness function offered based on...
In this paper, we consider the problem of modeling multiple-output nonlinear dynamic systems. We use linear model trees and ensembles of linear model trees to construct accurate models of nonlinear multiple-output dynamic systems, from input-output data. We show that it is beneficial to identify models with common structure for all outputs, utilizing interactions between the outputs. The operation...
In this paper, we present a new method for modeling production systems with discrete flows. This method is based on automatic knowledge to construct a mathematical model that accurately formalizes the behavior of the production system studied, from only (inputs / outputs) observable data, using the model parametric ARX.
Virtual environment is an important part of everyday life and it influences a psycho-emotional state of a user. This paper introduces affective state modeling using features of virtual 3D face. Observations of human affective state are done using preprocessed EEG (electroencephalogram) signals: excitement, meditation, frustration, engagement/boredom. The signals are measured using Emotiv EPOC device...
Many characteristics were distilled based on the vibration signal from gear-box Accelerated Life Testing. After analyzing the stability and sensitiveness of these characteristics, the factors, such as Clearance Factor, Crest Factor, Shape Factor and Root Mean Square, were selected and used. Then a residual useful life prediction model of gear-box based on stochastic filtering was established, which...
In this paper, interval fuzzy series forecasting based on GM (1, 1) model is studied. The grey differential equation of GM (1, 1) is improved to suite the interval fuzzy number. The development coefficient is taken as the weighted mean of the development coefficients of the left and right boundary points of the interval fuzzy number. It can indicate the integral development tendency of the interval...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.