Optimization and Control Strategies

On-line dynamic optimization and control strategy for improving the performance of batch reactors... 

Systems approach borrowed from the optimization and control communities can be used to achieve various other tasks of interest in multiscale simulation. For example, Hurst and Wen (2005) have recently considered shear viscosity as a scalar input/output map from shear stress to shear strain rate, and estimated the viscosity from the frequency response of the system by performing short, non-equilibrium MD. Multiscale model reduction, along with optimal control and design strategies, offers substantial promise for engineering systems. Intensive work on this topic is therefore expected in the near future. 

Lee, J. H., and Cooley, B. L., Optimal feedback control strategies for state-space systems with stochastic parameters, IEEE Trans. AC, in press (1998). 

In the recent years Simulated Moving Bed (SMB) technology has become more and more attractive for complex separation tasks. To ensure the compliance with product specifications, a robust control is required. In this work a new optimization bas adaptive control strategy for the SMB is proposed A linearized reduced order model, which accounts for the periodic nature of the SMB process is used for online optimization and control purposes. Concentration measurements at the raffinate and extract outlets are used as the feedback information together with a periodic Kalman filter to remove model errors and to handle disturbances. The state estimate from the periodic Kalman filter is then used for the prediction of the outlet concentrations over a pre-defined time horizon. Predicted outlet concentrations constitute the basis for the calculation of the optimal input adjustments, which maximize the productivity and minimize the desorbent consumption subject to constraints on product purities. 

The originally applied empirical strategies for the optimization of processes turned out to be of only limited value in the long term and for products of high economic value, such as therapeutic proteins, and the number of monitoring systems and control strategies continuously increased. The so-called low-level control based on temperature, pressure, pH and p02 [11]... 

In the first study, optimal component and control strategy parameters were derived to provide the best fuel economy on 4 individual drive cycles. The drive cycles included... 

Pareilleux and Chaubet (155,156) studied batch suspension cultures of apple cells and Medicago saliva cells, reporting comparable high yield and low maintenance coefficients. Bailey and Nicholson (157) employed in principle the same model structure. However, in order to describe also the changing fresh weight/dry weight ratio, product formation, and cell death and lysis, they extended the model. Two extra variables were added to allow the prediction of the extension phase and a more accurate prediction of the culture death phase caused by shear stress. Another two variables were introduced to describe product formation. In a later paper (158) the authors extended the model further to describe the influence of temperature. With this model an optimal temperature control strategy was predicted. 

The supercritical (SC) C02Brayton cycle has been optimized on paper and control strategies are under current study. Testing is being initiated on printed circuit heat exchanger components, which hold potential for recuperator size and cost reduction. An entire SC-CO2 Brayton cycle prototype will have to be built and tested to bring the technology to a state of... 

A theoretic study and computer simulation of model and control strategy for visual guidance of robot motion in dynamic environment is presented. Characteristics that make the visual guidance and motion control in dynamic environment distinct from that in static environment are discussed. The paper inspects the system attributes that must be taken account of and explores the inter-relations between these attributes. A conformable model of vision processing with the motion control of robot is developed. Computer simulation verifies the model and provides valuable insight toward the optimization of the process. 

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