Control design approach

A recent addition to the model-based tuning correlations is Internal Model Control (Rivera, Morari, and Skogestad, Internal Model Control 4 PID Controller Design, lEC Proc. Des. Dev., 25, 252, 1986), which offers some advantages over the other methods described here. However, the correlations are similar to the ones discussed above. Other plant testing and controller design approaches such as frequency response can be used for more complicated models. 

However, the stiffness/ill conditioning of the model (3.31) will strongly impact on the implementation of optimization controllers (e.g., a model predictive controller) (Baldea et al. 2010). On the other hand, for any choice of four flow rates as manipulated inputs (keeping the remaining one constant at its nominal value), the system is non-minimum phase (Kumar and Daoutidis 2002) and thus potentially closed-loop unstable with an inversion-based controller.3 As discussed in the previous section, a more systematic controller-design approach would... 

Traditional control design approaches, consider a fixed operating point in the hope that the resulting controller is robust enough to stabilize the system for different operating conditions. On the other hand, adaptive control incorporates the time-varying dynamical properties of the model (a new value of gas composition) and considers the disturbances acting at the plant (load power variation). 

Other plant testing and controller design approaches such as frequency response can also be used for more complicated models refer to Seborg, Edgar, and MeUichamp (2004) for more details. 

In this section, the process and control design approach presented in the last section is applied to a representative case example in polymer reactors. First, the example is addressed analytically, drawing results valid for a class of reactors. Then, the case of an industrial reactor is studied through simulations. The corresponding motion [4] and control [1, 38, 39] designs have been studied separately, meaning that the results can be compared. 

In this section, the proposed process-control design approach is illustrated with a representative starved emulsion semibatch polymerization and numerical simulations, with a model that emulates and industrial size reactor [11], Moreover, the simulation example corresponds to a scaled-up version of the theoretical-experimental calorimetrie estimation study presented before with a laboratory scale reactor [15]. 

Table H.l provides the key steps in a systematic procedure recommended here for design of plantwide control structures. It is based on the combined top-down/bottom-up approach of Larsson and Skogestad (2000) and Skogestad (2002) and the hierarchical organization that generally matches Fig. H.l. The proposed systematic plantwide control design approach consists of the four major steps shown in Table H.l.

When an installation is being planned, it is recommended that the API Standard 618 be reviewed in detail. The pulsation level for API 618 at Design Approach 1, the outlet side of any pulsation control device regardless of type, should be no larger than 2% peak-to-peak of the line pressure, or the value given by the following equation, whichever is less... 

Cooper, 1994. David Cooper and F. Alley, Air Pollution Control A Design Approach. 2" Edition, Wave and Press, Prospect Heights, IL, 1994,... 

Inherently safer design is a fundamentally different way of thinking about the design of chemical processes and plants. It focuses on the elimination or reduction of the hazards, rather than on management and control. This approach should result in safer and more robust processes, and it is likely that these inherently safer processes will also be more economical in the long run (Kletz, 1984, 1991b). 

Static pressure recovery method. The diameters are selected in such a way that the same static pressure is available before every connection. The duct reduction is selected in such a way that the gain of static pressure is in balance with the friction losses up to the next connection point. This method may result in fewer control devices at connection points or outlets. Low velocities and large diameters at the end of the system may be the result of this design approach. 

Mathews and Rawlings (1998) successfully applied model-based control using solids hold-up and liquid density measurements to control the filtrability of a photochemical product. Togkalidou etal. (2001) report results of a factorial design approach to investigate relative effects of operating conditions on the filtration resistance of slurry produced in a semi-continuous batch crystallizer using various empirical chemometric methods. This method is proposed as an alternative approach to the development of first principle mathematical models of crystallization for application to non-ideal crystals shapes such as needles found in many pharmaceutical crystals. 

Long time constants in the system and zone-to-zone interaction of the heaters complicated the controller design and tuning. The time available for experimental measurements was limited by the schedule of other experimental work to be performed by the extruder. The classic step response methods of tuning controllers would take on the order of hours to perform, and frequently disturbances in the polymer feed or in the ambient room conditions would invalidate the test. Consequently, a mathematical rather than an empirical approach was desirable. 

We have given up the pretense that we can cover controller design and still have time to do all the plots manually. We rely on MATLAB to construct the plots. For example, we take a unique approach to root locus plots. We do not ignore it like some texts do, but we also do not go into the hand sketching details. The same can be said with frequency response analysis. On the whole, we use root locus and Bode plots as computational and pedagogical tools in ways that can help to understand the choice of different controller designs. Exercises that may help such thinking are in the MATLAB tutorials and homework problems. 

In terms of controller design, we can take an entirely analytical approach when the system is simple enough. Of course, such circumstances are not common in real life. Furthermore, we often have to compromise between conflicting criteria. For example, we cannot require a system to have both a very fast rise time and a very short settling time. If we want to provide a smooth response to a set point change without excessive overshoot, we cannot also expect a fast and snappy initial response. As engineers, it is our job to decide. 

A more elegant approach than direct synthesis is internal model control (IMC). The premise of IMC is that in reality, we only have an approximation of the actual process. Even if we have the correct model, we may not have accurate measurements of the process parameters. Thus the imperfect model should be factored as part of the controller design. 

Shanley, A., Thomas, P., Wagner, M. V., Ciurczak, E. Lessons from Heparin. Avoiding future drug quality disasters will require closer control over raw materials, use of more powerful analytics and IT, and a Quality by Design approach. Pharmaceutical Outsourcing, 2008. http //www.pharma manufacturing.com/articles/2008/123.html. Accessed on 17th July 2012. 

Morari and coworkers (Garcia and Morari, Ind. Eng. Chem. Process Des. Dhv. Vol. 21, p. 308, 1982) have used a similar approach in developing Internal Model Control (IMC). The method is useful in that it gives the control engineer a different perspective on the controller design problem. 

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