Advanced control strategies

Host computers. These are the most powerful computers in the system, capable of performing func tions not normally available in other units. They act as the arbitrator unit to route internodal communications. An operator interface is supported and various peripheral devices are coordinated. Computationally intensive tasks, such as optimization or advanced control strategies, are processed here. 

A basic use of a process model is to analyse experimental data and to use this to characterise the process, by assigning numerical values to the important process variables. The model can then also be solved with appropriate numerical data values and the model predictions compared with actual practical results. This procedure is known as simulation and may be used to confirm that the model and the appropriate parameter values are "correct". Simulations, however, can also be used in a predictive manner to test probable behaviour under varying conditions, leading to process optimisation and advanced control strategies. 

For chemical processes (without cells) several advanced control strategies have been developed, some of which can be applied to bioprocesses and, especially, in animal cell cultures. Two of them are described below. 

Advanced Control Strategies for Chemical Processes A Review... 

Consider advanced control strategies such as model-based control (MPC). 

Advanced control strategies require a model that accurately represents the behavior of the process. Model identification involves determining an appropriate model structure, performing experiments, collecting data that allow identification of model parameters, and estimating the parameters. There are several ways to model crystallization processes, but a review of parameter estimation is beyond the scope of this chapter. A discussion of the most relevant methods of model identification for continuous crystallizers is given below. 

Figure 4.19 presents an advanced control strategy for the inline dilution as implemented within the large-scale chromatography systems. The inline dilution controller takes into account the actual set point for conductivity SP COND and maximal allowed pressure SP PRESS of the chromatography system. The conductivity controller (1) corrects the inline dilution factor, that is, the ratio between the flow rates... 

The mode of operation (batch, continuous) and the use of a dedicated or a multipurpose plant is crucial for the choice of an appropriate ISPR configuration. The successful production of bulk products such as lactic acid requires an optimized dedicated system. This production plant has special equipment and advanced control strategies and is not very flexible. Generation of additional by-products has to be avoided. High added value, low volume products such as fine chemical or natural flavors are mostly produced in multipurpose plants. Investment in additional equipment or modifications of the reaction vessels is more difficult to justify, if just a few products need the application of ISPR. In this case, the less complex ISPR configurations 1 and 3 are preferred. Fiuthermore, the outlet of the production should also be easily adjustable to the market demand. 

As is well-known in practice, the protein folding properties and, hence the product quality is dependent on the cultivation conditions of the host organism. Thus, in order to guarantee products within narrow specification limits, the production process must be kept under tight control (4). An essential prerequisite is accurate monitoring of the process state and an optimization of the trajectories of the key process variables. Advanced control strategies require to predict the process behaviour at least over time horizons which are needed to influence the process so that the state variables will not escape from the acceptable intervals. Prediction, however, means that the process has to be modelled. 

The GT-off design performance has also been investigated by Naqvi et al [76], The use of C02-rich stream gas turbine is also included in the analysis, which accounts for 14% of the electric gross power produced. The net electric efficiency is around 52% in the case of maximum solid temperature of 1200°C (Figure 5.26), and the electric efficiency decay due to the part-load operation is lower than that in the conventional combined cycle (higher than 94% of the nominal electrical efficiency in the case of 54% of full load) if an advanced control strategy is adopted. 

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