This paper investigates multiple alternatives to predict environmental parameters (temperature and relative humidity) inside an intelligent container with the aim of the supervision of cool chains. A wireless sensor network will help us to measure those parameters in some distributed points of the closed space. To achieve the aim of fault detection and also total energy saving in the sensor net...

In this paper, the problem of estimating uncertainty regions for identified models is considered. A typical approach in this context is to resort to the asymptotic theory of Prediction Error Methods (PEM) for system identification, by means of which ellipsoidal uncertainty regions can be constructed for the uncertain parameters. We show that the uncertainty regions worked out through the asympt...

Modeling and identification for high dimensional (i.e. signals with many components) data sets poses severe challenges to off-the-shelf techniques for system identification. This is particularly so when relatively small data sets, as compared to the number signal components, have to be used. It is often the case that each component of the measured signal can be described in terms of few other m...

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of t...

This paper focuses on a comparative study of a new estimation method applied on a wireless sensor network, installed in a closed space container. We would like to pick out the best method among the existing identification methods such as ARX, ARMAX, OE, BJ and SS. we are looking for a way to reduce power consumption due to measuring and transmitting data in some desired sensor nodes (DSNs) and ...

1 Corresponding and presenting author: Y. K. Wong, Tel: (852) 2766-6140, Fax: (852) 2330-1544, Email: [email protected] Abstract The needs of accuracy of machines are strictly increasing for the manufacturing processes. It is costly to use high precision machine to achieve the goal. Therefore, if the forecasting of errors can be obtained from the gathered past error values, it allows the co...