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In this paper by applying the direct continuous-time system identification methods an accurate and reliable control oriented model of the conductivity in the polishing phase of the purification process of the nimotuzumab, a monoclonal antibody, is derived. A brief introduction to the theoretical aspects of the direct continuous-time system identification methods is presented. The complete direct system identification procedure, from the design of the experiment to model validation is developed. For this purpose, the CONTSID toolbox is used. The model validation results show that the model obtained reproduces with high accuracy the observed data, and therefore it can be used in the design of control systems and/or for prediction purposes [ABSTRACT FROM PUBLISHER]

In this paper by applying system identification tools a neural network model of an irrigation main canal pool is obtained. The complete system identification procedure, from experimental design to model validation, taking into account prior physical information, is developed. It is established that a nonlinear model with NARX structure can adequately describe the dynamic behavior of an irrigation main canal pool. The model validation results show that the model obtained reproduces with high accuracy the observed data and therefore it can be applied in the design of nonlinear control systems and/or for prediction purposes. [ABSTRACT FROM PUBLISHER]

The steel industry is among the companies with highest energy consumption due to the heating processes in their production. Furnaces used for slabs reheating in this industry require a good regulator to control temperature in each zone optimizing combustible consumption. Considering the complex and variable dynamic behavior of furnace temperature, this paper proposes a modification of the Smith predictor scheme, combined with a gain scheduled fuzzy block idea, for controlling the soaking zone temperature in a steel slab-reheating furnace. For this purpose, a soaking zone temperature dynamic model is obtained from an identification procedure resulting in a second order plus time delay transfer function, where the dominant time delay varies with respect to the slab thickness. The performance of the proposed method is compared against the filtered Smith predictor and the classic one. The best results were obtained using the fuzzy gain-scheduled Smith predictor achieving a smooth transition in each operation point. [ABSTRACT FROM PUBLISHER]