Economic Control Objectives

While safe operation is a necessary requirement to run a process it 

To control the economic objectives we must have measurements and manipulated variables. However, in the example reactors we have looked at so far it should be clear that tve have only a limited number of manipulated variables, especially after we have taken care of the heat management issues. How is it then possible to achieve any level of economic control of a reactor The answer lies in a concept introduced by Shinnar (1981) called partial control. In short it means that only a few dominant variables in the process (e.g., temperatures, key components) are identified, measured, and controlled by feedback controllers. Then, by varying the setpoints for the dominant variables, it becomes possible to position the process such that all the important economic variables stay within acceptable ranges. We will elaborate more on this important concept in the next section but first we introduce the classification of reactor variables used by Shinnar. 

For the discussions around partial control it is convenient to classify the measurements further. For control purposes we pay particular attention to the variables Yd (d for dynamic) that are measured continu- 

We can make a similar classification around U and W. For instance, control valves belong to the set UB. whereas the regeneration of a packed-bed catalyst would be classified as JX,. Similarly, measurements of the reactor feed flow and temperature belong to W while a once-per-shift analysis of the reactor feed composition belongs to W,. 

Control engineers know that it takes one manipulated variable for each measured variable we wish to control to setpoint. When the number of controlled variables equals the number of manipulated variables we pair up the different variables and use PI controllers for regulation. Sometimes we are fortunate to have more manipulated variables than control specifications. We can then optimize the use of the manipulators while controlling to setpoint (e.g., valve position control). Sometimes, however, the number of control objectives exceeds the number of available manipulators and we cannot control all variables to setpoint. This is when the concept of partial control is useful. 

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During the course of the subsequent steps, we may find that we lack suitable manipulators to achieve the desired economic control objectives. Then we must change the process design to obtain additional handles. For example, we may need to add bypass lines around heat exchangers and include auxiliary heat exchangers. 

Once we identify the dominant variables, we must also identify the manipulators (control valves) that are most suitable to control them. The manipulators are used in feedback control loops to hold the dominant variables at setpoint. The setpoints are then adjusted to achieve the desired production rate, in addition to satisfying other economic control objectives. 

Hence the key economic control objectives for polymer reactors are typically average molecular weight, polydispersity, viscosity, composition, partical size distribution, and production rate (plus color, phase... 

The reaction studied in Section 2.2 has two reactants and therefore offers the possibility of adjusting the compositions of the reactants in the reactor to achieve some economic or control objective. In this section we first find the cost of operating single and multiple CSTR processes to achieve a specified conversion. Then we design an alternative process consisting of a reactor and a distillation column that separates product C from the unreacted A and B in the reactor effluent and recycles them back to the reactor. 

Control objectives for a chemical process originate from certain regulation tasks (i.e. product quality control, material balance control, safety, environmental regulations, etc.) and economic objectives (i.e. optimizing the economic performance). Such a classification of control objectives automatically formulates the different design activities for the regulatory and optimizing control structures. 

Step 9. Optimize economics and improve dynamic controllability. While a temperature control system for the CSTR is in place, its se int needs to be established. To meet the second control objective, which seeks to maximize conversion, a cascade controller is installed in which the setpoint of the reactor temperature controller (TC on V-2) is adjusted to control the concentration of B (CC) in the reactor effluent. If the reaction is irreversible, conversion is maximized by operating the reactor at the highest possible temperature, making this controller unnecessary. 

A distributed control system may involve the use of microcomputers at the local level and the use of more powerful rruchines to coordinate overall plant control objectives. In this context, it has been suggested that process control might be described better as process management." " Local control of the operation of individual separators is still important but, with the use of distributed control, reliability is maintained (microcomputers are dedicated to particular process units) while overall technical and economic objectives are pursued (mainframe computers can perform complex on-line/off-line optimization). The advantage to distributed control is that it makes effe ve use of current technology and provides a framework within which control and optimization developments can be implemented. These developments probably will include better simulation and optimization routines that will help to assess the current state of the process plant and to suggest improvements. 

Generally speaking, a chemical process that shows poor ability of meeting control objectives gives rise to missing opportunities with respect to economic performance and satisfaction of product specifications. This fact may imply the existence of a trade-off between those processes designed with respect to control performance considerations... 

The above formulation enables the study of control structures with unequal number of controlled and manipulated variables. As already mentioned, lack of sufficient input capacity may hinder the flowsheet from satisfying the underlined control objectives completely. The imposed ranking through the selected objective function would prioritise the importance of each control objective and guide the control system through the partial satisfaction of the control targets. The use of the input resources is closely associated with an economic factor (e.g., cost of steam and fresh material). Therefore, the most competitive way to compensate for the effects of disturbances relies on the efficient use of the available input capacity. In... 

Assumption 5 The economic objectives of the process, both implicit and explicit, can be translated to control objectives. Therefore, each objective can be associated with a measurable process variable. 

Based on the steady-state optimization for each module, only one active control constraint is identified for the HDA process - the reactor inlet temperature. The nine-step procedure to generate a plantwide control structure developed by Luyben et al.[7] is now applied to each module. These steps are (i) establish the control objectives, (ii) determine the control degrees of freedom, (iii) establish energy management, (iv) set the production rate, (v) control the product quality, (vi) fix a flow in every recycle loop and control inventories, (vii) check component balances and (viii) control individual imit operations, and (ix) optimize the economics or improve the dynamic controllability. The number of control degrees of freedom identified for each module (referred to by their respective dominant unit operation) are as follows reactor 10, product column 10, and recycle column 5. 

A. State the plant production, economic, and control objectives, including composition and production rates of all products. 

The most straightforward means of evaluating control strategies using the steady-state simulation approach is via an economic profitability function. Working in profit makes assessment of the trade-offs between various control objectives much easier. Typically, the profitability function is given as... 

In our example, the tray 20 temperature control objective would be replaced with the TVP objective. For the feed composition change, the profitability of the tray 20 temperature objective is 126 729 per day and the profitability of the TVP objective is 128 611 per day. Therefore, this indicates that, for this disturbance, there is a positive economic driver to control the TVP directly of about 1880 per day. By performing this same type of analysis around the range of potential disturbances and weighting the benefits as per the likelihood of the disturbance occurring, we can determine a benefit number for the analyser installation. Of course, this benefit must be balanced against the installation and maintenance cost of the TVP analyser. 

Wear is an economic consideration. Wear resistance generally, but not always, is inversely related to friction level and other desirable performance charactenstics within any class of friction matenal. The objective is to provide the highest level of wear resistance in the normal use temperature range, a controlled moderate increase at elevated temperatures, and a return to the original lower wear rate when temperatures again return to normal. Contrary to common behef, maximum wear life does not require maximum physical and mechanical properties. 

The immediate objective of an advanced control effort is to reduce the variance in an important controlled variable. However, this effort must be coupled with a commitment to adjust the target for this controlled variable so that the process is operated closer to the constraint. In large throughput (commodity) processes, very small shifts in operating targets can lead to large economic returns. 

The object of a process control system is to make economic and sound decisions about the actions affecting the process. Data concerning the variations in process performance are collected and analyzed and decisions taken as to whether action on the process is or is not necessary to maintain production of conforming product (see Figure 9.1). However, process control and process capability are not one and the same, as illustrated in Figure 9.5. 

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