The issue of modeling and control of multivariable chemical process systems using the dynamic version of a popular multivariate statistical technique, namely, projection to latent structures (partial least squares or PLS) is addressed. Discrete input -output data are utilized to construct a projection-based dynamic model that captures the dominant features of the process under study. The smcture of the resulting model enables the synthesis of a multiloop control system. In addition, the design of feedforward control for multivariable systems using the dynamic PLS framework is also presented. Three case studies are used to illustrate the modeling and control of multivariable linear and nonlinear systems using the suggested approach.

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Methods of implementing an input-constrained, nonlinear, model-predictive controller

This paper proposes a simple method to synthesize a proportional-integral-derivative (PID) type controller that is capable of providing the best possible performance for regulating stochastic disturbances and/or set-point tracking. This novel strategy requires no a priori information about the open-loop process or noise models. Input-output data from closed-loop experimental tests (e.g., through natural or induced set-point changes) will be used to estimate the closed-loop servo and disturbance models, which are then utilized to arrive at "optimal" PID controller settings. Several measures of the performance and robustness are computed alongside to aid in the process of controller tuning. The efficacy of the proposed method is demonstrated using representative case studies.

In this paper, a mathematical model based on the diffusion of nutrients is developed by considering the physiological changes accompanying the growth of avascular tumour. Avascular tumour growth involves the formation of three different zones namely proliferation, quiescent and necrotic zones. The main processes on which avascular tumour growth depends are: (i) diffusion of nutrients through the tumour from the contiguous tissues, (ii) consumption rate of the nutrients by the cells in the tumour, and (iii) cell death by apoptosis and necrosis. In the model, we consider the tumour to be spherical and the principal nutrients responsible for its growth are oxygen and glucose. By solving for the concentration profiles using the model developed, we are able to compute the radii of the quiescent and necrotic zones as well as that of the tumour. The proposed model is also validated using in vitro tumour growth data and Gompertzian empirical relationship parameters available in the literature. Our model is also successful in capturing the saturated volume of the avascular tumour for different nutrient concentrations at the tumour surface.Dans cetteétude, nousélaborons un modèle mathématique fondé sur la diffusion des nutriments en tenant compte des changements physiologiques qui accompagnent la croissance d'une tumeur avasculaire. La croissance d'une tumeur avasculaire comprend la formation de trois zones différentes,à savoir la zone de prolifération, la zone quiescente et la zone nécrotique. Les principaux processus dont dépend la croissance d'une tumeur avasculaire sont les suivants: (i) la diffusion des nutriments dans la tumeur partant des tissus adjacents, (ii) le taux de consommation des nutriments par les cellules dans la tumeur, et (iii) la mort cellulaire par apoptose et nécrose. Dans le modèle, nous considérons la tumeur commé etant sphérique et les principaux nutriments responsables de sa croissance, l'oxygène et le glucose. En déterminant les profils de concentration au moyen du modèleélaboré, nous sommes en mesure de calculer le radius des zones quiescente et nécrotique, de même que celui de la tumeur. Le modèle proposé estégalement validé au moyen des données sur la croissance des tumeurs in vitro et des paramètres des relations empiriques gompertziennes disponibles dans la documentation. Notre modèle réussitégalementà saisir le volume saturé de la tumeur avasculaire pour différentes concentrations de nutrimentsà la surface de la tumeur.