Abstract-This paper deals with traffic modeling and control design for high-frequency metro lines. A complete discrete-event traffic model pointing out the natural instability of metro lines is to-implement state feedback traffic control algorithms are depresented. The traffic stability properties are analyzed and easysigned, which guarantee the system stability. Simulations illustrate the methodology.H

This article presents an introduction to the use of neural network computational algorithms for the dynamic modeling of bioprocesses. The dynamic neural model is used for the prediction of key fermentation variables. This relatively hew method is compared with a more traditional prediction technique to judge its performance for prediction. Illustrative simulation results of a continuous stirred tank fermentor are used for this comparison. It is shown that neural network models are accurate with a certain degree of noise immunity. They offer the distinctive ability over more traditional methods to learn very naturally complex relationships without requiring the knowledge of the model structure.

Reaction systems constitute a class of nonlinear dynamical systems relevant in many engineering fields such as chemical engineering, biotechnology and ecology. In this paper, we address the problem of the reduction of the order of such systems under the assumption that some reaction rates are much faster than the others. This can be achieved through a change of coordinates which transforms the system in a two-time-scale standard form.

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