Conversion open-loop

Figure 4. Simulated open-loop conversion of vinyl acetate system at initiator concentration of 0.005 mol/L H20 and 50°C (a) S = 0.06 mol/L (b) S =...

What are the control implications of this analysis The first conclusion is that autothermal systems (no furnace) have two or more steady states. There is also a good chance that the normal operating point corresponds to the intermediate steady state that is open-loop unstable. This is certainly the case when the reactor is operated at less than 100 percent conversion. 

Control systems may be classified from their signal flow diagrams as either open-loop systems or closed-loop systems depending on whether the output of the primary control circuit is fed back to the controlling component. As Fig. 2 suggests, the typical control circuit consists of sequential arrays of components deployed about the process under control. If the controller is not apprised of the behavior of the controlled variable, the control system is an open-loop one. Conversely, if the measuring means on the controlled variable sends its signals back to the controller so that the behavior of the controlled variable is always under the scrutiny of the controller, the system is a closed-loop or feedback control system. 

Fig. 12.20 O2 conversion data versus temperature for the oxidation of CH4 for three microreactor channels. Open-loop temperature control was used in this experiment with each heater set to the same heater voltage. The temperature used for the plot is the average of the measured RTD temperatures. These results come from one AIMS experiment with three...

Kipaiissides et al. [36] have applied suboptimal control to the CSTR emulsion polymerization of vinyl acetate. A mathonatical model was used to develop a simulation of the polymerization process. Verification of the model was done by open-loop bench-scale polymerization. Closed-loop control of monomer conversion via manipulation of both monoma and initiator flow rates was... 

Process models are also important components of reactor control schemes. Kiparissides et al. [17] and Penlidis et al. [16] have used reactor models for control simulation studies. Particle number and size characteristics are the most difficult latex properties to control. Particle nucleation can be very rapid and a strong function of the concentration of free emulsifier, electrolytes and various possible reagent impurities. Hence the control of particle number and the related particle surface areas can be a difficult problem. Even with on-line light scattering, chromatographic [18], surface tension and/or conversion measurements [19], control of nucleation in a CSTR system can be difficult. The use of a pre-made seed or an upstream tubular reactor can be utilized to avoid nucleation in the CSTR and thereby imjHOve particle number control as well as increase the number of particles formed [20-22]. Figures 8.6 and 8.7 illustrate open-loop CTSR systems for the emulsion polymerization of methyl methacrylate with and... 

In the second part of this chapter, focus was on control of continuously operated RD processes. So far most control studies focus on processes that are operated close to chemical equilibrium. Emphasis was on the well-known esterification and etherification systems. The methods employed are similar to non-RD column control. It is worth noting that this is consistent with our conclusions on open-loop dynamics as drawn above. Additional problems may rise in indirect control schemes, where product compositions are inferred from temperature measurements. It was shown that these problems can be handled if in addition some direct or indirect measure of conversion is taken into account. 

Conversely, procedure B, where the user has to define the whole existence of Jacobian matrix, is generally four times faster than procedure A. It requires about 2 s to simulate 6 s in open-loop and about 3.5 s to simulate the closed-loop scenario. 

Figure 8.5 Monitoring a semibatch emulsion polymerization reaction of VAc/BA by means of an open-loop observer based on calorimetric measurements, (a) Conversion and (b) copolymer composition.

Extensions of Kalman filters and Luenberger observers [131 Solution polymerizations (conversion and molecular weight estimation) with and without on-line measurements for A4w [102, 113, 133, 134] Emulsion polymerization (monomer concentration in the particles with parameter estimation or not (n)) [45, 139[ Heat of reaction and heat transfer coefficient in polymerization reactors [135, 141, 142] Computationally fast, reiterative and constrained algorithms are more robust, multi-rate (having fast/ frequent and slow measurements can be handled)/Trial and error required for tuning the process and observation model covariance errors, model linearization required The number of industrial applications is scarce A critical article by Wilson eta/. [143] reviews the industrial implementation and shows their experiences at Ciba. Their main conclusion is that the superior performance of state estimation techniques over open-loop observers cannot be guaranteed. 

As discussed in Section 8.3.2, in addition to the fast and frequent on-hne measurement, some measurements may be available at infrequent and/or irregular times and with significant delays. For example, there may be a combination of MWDs and PSDs measured off-line by chromatographic methods and monomer concentrations measured in real time by spectroscopic methods. In these cases, the so-called multi-rate state estimators maybe applied. In these estimators, the fast measurements are used to estimate the state variables that are observable, while estimation of the non-observable variables is obtained in open-loop mode. When the (infrequent) measurement becomes available, the close-loop estimator is used. Ellis et al. [102] and Mutha etal. [108] used a multi-rate EKF to estimate monomer conversion and average molecular weights in the solution polymerization ofMMA. 

Monomer conversion can be adjusted by manipulating the feed rate of initiator or catalyst. If on-line M WD is available, initiator flow rate or reactor temperature can be used to adjust MW [38]. In emulsion polymerization, initiator feed rate can be used to control monomer conversion, while bypassing part of the water and monomer around the first reactor in a train can be used to control PSD [39,40]. Direct control of surfactant feed rate, based on surface tension measurements also can be used. Polymer quality and end-use property control are hampered, as in batch polymerization, by infrequent, off-line measurements. In addition, on-line measurements may be severely delayed due to the constraints of the process flowsheet. For example, even if on-line viscometry (via melt index) is available every 1 to 5 minutes, the viscometer may be situated at the outlet of an extruder downstream of the polymerization reactor. The transportation delay between the reactor where the MW develops, and the viscometer where the MW is measured (or inferred) may be several hours. Thus, even with frequent sampling, the data is old. There are two approaches possible in this case. One is to do open-loop, steady-state control. In this approach, the measurement is compared to the desired output when the system is believed to be at steady state. A manual correction to the process is then made, based on the error. The corrected inputs are maintained until the process reaches a new steady state, at which time the process is repeated. This approach is especially valid if the dominant dynamics of the process are substantially faster than the sampling interval. Another approach is to connect the output to the appropriate process input(s) in a closed-loop scheme. In this case, the loop must be substantially detuned to compensate for the large measurement delay. The addition of a dead time compensator can... 

The ability of the controller to handle process disturbances was examined by simulating abrupt variations in feed quality. This was simulated by increasing the concentration of inhibitor in the monomer from zero to 10 ppm. The variation in feed quality is a common problem in industrial practice and results from the deliberate addition of inhibitor to monomer to prevent premature polymerization. If monomer purification to remove inhibitor is not done (and it often is not in commercial operations), the switching of monomer feed tanks can produce undesirable and unexpected effects on the process outputs. In the open loop, the increase in inhibitor concentration from zero to 10 ppm causes a drop in the monomer conversion from 0.247 to 0.169. The particle size output also experiences a decline from 0.762 to 0.737. The reduction in polymerization rate is a direct result of the decreased initiator flux into the polymer particles, and the drop in particle size reflects the diminished... 

Optimization of (semi)batch kettle operation will include considerations of kettle time versus conversion, kettle time versus monomer recovery cost, and the potential for variations in polymerization temperature within a batch to achieve desired product properties. Open-loop trajectories may be determined... 

The closed loop and open loop reactor dynamics are compared in Figs. 9 and 10, for a step decrease in the reactor pressure. A SISO controller was tuned to control the inlet temperature of the first bed, Toi, tl ugh the by-pass valve (see Fig. 1). When the reactor is operated without feedback control, the sudden reduction in the pressure leads to a decrease in Ae heat generation rate, the temperature Touti (and consequently Toi) decreases and the reactor moves to a lower (extinguished) steady state. This effect can be serai in Fig. 9, where the overall temperature rise drops from 230 C to 12 °C. Conversely, when the feedback control loop is included, the overall temperature rise shows a significantly lower decrease (from 230 to 199°C) as a consequence of the gradual reduction of the cold by-pass (Fig. 10). 

A similar behaviour is found for the case of an increase in the ammonia contraits at the inlet of the converter. In fact, when the molar fiaction of ammonia in the feed stream increases, the equilibrium shifts to the reactants and the heat generation rate decreases. If the reactor is being operated under open loop, an extinction phenomenon rqipears due to the autothermal operation of the converter (Fig. 11). Under closed loop operation, the control action leads to a decrease in the cold by-pass fraction (Fig. 12). As a result, the reactor remains at the upper branch of the curve shown in Fig. 2 (ignited steady-state) and the outlet conversion drops slightly. 

Control of the SCR system could be either open-loop or closed-loop [31, 32]. Basic open-loop control will be robust and not have any stability problems [32] however, it will be difficult to achieve very high NOx conversions. Song and Zhu [32] estimated that maximum ca 75 % NOx conversion would be possible with... 

The term open-loop unstable is also used to describe process behaviour. Some would apply it to any integrating process. But others would reserve it to describe inherently unstable processes such as exothermic reactors. Figure 2.21 shows the impact that increasing the reactor inlet temperature has on reactor outlet temperature. The additional conversion caused by the temperature increase generates additional heat which increases conversion further. It differs from most non-self-regulating processes in that the rate of change of PV increases over time. It often described as a runaway response. Of course, the outlet temperature will eventually reach a new steady state when aU the reactants are consumed however this may be well above the maximum permitted. 

Polymerization reactors are well known both theoretically and experimentally to exhibit multiple steady states [26, 27] and in some cases they may also exhibit oscillations in terms of monomer conversion and polymer particle diameter [28]. In other cases it may be necessary to choose an open-loop unstable state as the reactor operating point. Furthermore, polymerization reactors can be highly exothermic and result in reactor thermal runaway. 

An automated pilot-scale 1-litre experimental polymer reactor system with facilities for on-line measurement of flow rate, temperature and density has been set up by Chien and Penlidis (1994a, b). These authors describe a set of open-loop process identification experiments and closed-loop control experiments performed on this system where monomer conversion is controlled in the presence of reactive impurities using the initiator flow rate as the manipulated variable. 

The open-loop observer formed by Equations 7.23,7.27, and 7.28 has been successfully used to estimate the unreacted amounts of monomers in different monomer systems under different conditions [25-29]. Once the unreacted amounts of the monomers (Al and A ) are estimated during the course of the polymerization, the conversion and copolymer compositions can be readily estimated for batch and semibatch reactors. The accuracy of the estimation depends on the reactivity ratios and enthalpies of polymerization for each monomer that can be obtained experimentally or are available in the literature. 

Othman et al. [86] proposed a closed-loop method to control molecular weight. They used NIR to estimate conversion. They developed a nonlinear estimator to get the reaction rate necessary for the control loop. This method reUes on the quality of off-line measurements necessary for NIR calibration. They used nonlinear high-gain observers to identify model parameters and the reaction rates which were used to obtain desired monomer feeds to keep constant. This feedback control produced high molecular masses which could not be achieved in open-loop cases but the approach still relies on the quality of the model. 

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