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.
SUMMARYThe commonly used state-space models for the traffic description of urban underground railway lines are not suitable for practical on-line control. On the other hand, the proposed orginal linear formulation is very convenient for optimal state feedback control implementation. Results of simulations relative to a theoretical line as well as to the Brussels Railway lines show the benefit to be expected using this new formulation for on-line traffic control.
There are a variety of control strategies that one may consider for mill circuit control and often several methods for implementing each strategy.Ideally, the control strategy selected and methodology used in it's implementation should not only optimize circuit performance in terms of productivity but also be able to optimize quality.A linear quadratic multivariable controller has been applied to milling circuits and these goals successfully accomplished.The results are a stable circuit with mill and separator optimized, producing a consistent quality product of a predictable fineness. This enables one to use cement quality as the single circuit control set point.
An adaptive control algorithm has been implemented on a biomethanation process to maintain propionate concentration, a stable variable, at a given low value, by steering the dilution rate. It was thereby expected to ensure the stability of the process during the startup and during steady-state running with an acceptable performance. The methane pilot reactor was operated in the completely mixed, once-through mode and computer-controlled during 161 days. The results yielded the real-life validation of the adaptive control algorithm, and documented the stability and acceptable performance expected.
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