Open-loop process-control operation

Here the critical process variables are identified from the selected list of process variables. The model library or process data (if available) are used for this analysis. To perform the sensitivity analysis, the process operational model is simulated through ICAS-MoT. The effect of each process variable on the target product properties is analyzed systematically through open loop simulation. The operational objectives have to be assessed first. If an operational objective is not achieved, then the process variables have to be analyzed. The variables which violate the operational limit and have a major effect on the product quality are considered as the critical process variables. For some of the variables which can not be modeled the sensitivity analysis has to be performed qualitatively through inference from the knowledge base and/or by the use of process data. All the critical process variables need to be monitored and controlled. For some of the critical variables that can not be measured in real time, other correlated properties have to be measured so that all critical variables can be measured and controlled by using the correlations to the measurable variables. 

The previous workshop demonstrated that capacity-dominated processes have significant disturbance rejection (attenuation) properties without requiring any form of process control. This is called open-loop attenuation. Controllers can usually increase the attenuation of process systems. When operated in automatic , the additional attenuation is called closed-loop attenuation. When in manual , the system behaves as it would without the controller present. 

An open-loop system positions the manipulated variable either manually or on a programmed basis, without using any process measurements. This operation is acceptable for well-defined processes without disturbances. An automanual transfer switch is provided to allow manual adjustment of the manipulated variable in case the process or the control system is not performing satisfac torily. 

Open-Loop versus Closed-Loop Dynamics It is common in industry to manipulate coolant in a jacketed reacdor in order to control conditions in the reacdor itself. A simplified schematic diagram of such a reactor control system is shown in Fig. 8-2. Assume that the reacdor temperature is adjusted by a controller that increases the coolant flow in proportion to the difference between the desired reactor temperature and the temperature that is measured. The proportionality constant is K. If a small change in the temperature of the inlet stream occurs, then depending on the value or K, one might observe the reactor temperature responses shown in Fig. 8-3. The top plot shows the case for no control (K = 0), which is called the open loop, or the normal dynamic response of the process by itself. As increases, several effects can be noted. First, the reactor temperature responds faster and faster. Second, for the initial increases in K, the maximum deviation in the reactor temperature becomes smaller. Both of these effects are desirable so that disturbances from normal operation have... 

As stated in the previous section, the major reactant feed was chosen as the manipulated variable. In the trial this feed was subjected to a pseudo-random binary sequence (PRBS) signal in an open loop operation of the process. The results of the trial, plotted in Fig. 2, show a strong -- but delayed -- cross-correlation between the manipulated feed rate and the reactor temperature. Using techniques described by Box and Jenkins (2), a transfer function relating the manipulated variable to the control variable of interest can be developed. The general form of this transfer function is... 

One reason why this approximation works is that process unit operations are generally open-loop stable, and many are multi-capacity in nature. Reminder Underdamped response of the system is due to the controller, which is taken out in the open-loop step test. 

Most chemical processes exhibit stable open-loop behavior. However, there are some important processes, such as chemical and biological reactors, that might be operated around an unstable steady state. The tuning of PID controller forunstable systems has recently attracted attention [16-19], Lee et al. [18] have presented a powerful IMC-based tuning methodology that appears to surpass most of available tuning techniques for unstable systems with low order dy-... 

Most processes are open loop stable, also called self-regulating, i.e. stable without any controllers on the system. This means that after a change in the system caused by either a disturbance or by a deliberate change in a manipulated variable, the process will come to a new stable operating condition, i.e. a new steady state. This is not necessarily the... 

What makes controller design challenging is that all real processes can be made closed loop unstable when a controller is implemented to steer the process to specified operating conditions. In other words, a process which is open loop stable and therefore will come to a new, although not the desired, steady state after a disturbance may become unstable when a controller is implemented to steer the process towards the desired steady state. Stability is therefore of vital concern in all control systems. 

We will first concentrate on studying the process dynamics, so let us consider a numerical experiment that consists of starting a dynamic simulation of the process from initial conditions that are slightly perturbed from the nominal, steady-state values of the state variables. Although material holdups are stabilized using the proportional controllers in Equation (4.40), in view of the process-level operating objective stated above, this can be considered an open-loop simulation. 

Chemical reactors are inherently nonlinear in character. This is primarily due to the exponential relationship between reaction rate and temperature but can also stem from nonlinear rate expressions such as Eqs. (4.10) and (4.11). One implication of this nonlinearity for control is the change in process gain with operating conditions. A control loop tuned for one set of conditions can easily go unstable at another operating point. Related to this phenomenon is the possibility of open-loop instability and multiple steady states that can exist when there is material and/or thermal recycle in the reactor. It is essential for the control engineer to understand the implications of nonlinearities and what can be done about them from a control standpoint as well as from a process design standpoint. 

We noted earlier in this chapter that many reactions in the chemical industries are exothermic and require heat removal. A simple way of meeting this objective is to design an adiabatic reactor. The reaction heat is then automatically exported with the hot exit stream. No control system is required, making this a preferred way of designing the process. However, adiabatic operation may not always be feasible. In plug-flow systems the exit temperature may be too hot due to a minimum inlet temperature and the adiabatic temperature rise. Systems with baekmixing suffer from other problems in that they face the awkward possibilities of multiplicity and open-loop instability. The net result is that we need external cooling on many industrial reactors. This also carries with it a control system to ensure that the correct amount of heat is removed at all times. 

Improved performance is achieved with a more complex operation and layout of the process, which requires precise process design and control - especially when a recycling of the section IV outlet is applied and a second point of mixing at the desorbent port is implemented. An open-loop operation without eluent recycling between sections I and IV is more robust, especially when regeneration of the adsorbent is necessary. 

A trimmable resistor network in the feedback loop of the operational amplifier OP2 is aligned during the calibration process. The total resistance of the resistor network is increased by opening fusible links (Fig. 6.2.11). A test calibration is not possible. At the end of the hole trimming a special link is fused to deactivate the complete control logic for safety reasons. Consequently, accidental trimming is prevented. 

Qince the first large sulfur dioxide control system was installed at the Battersea plant in London, it has taken almost 50 yrs for calcium-based scrubbing technology to become commercially acceptable. In 1926, the 125 MW coal-fired Battersea power plant was equipped with a spray packed tower and final alkaline wash section which removed more than 90% of the sulfur dioxide and particulate (I). Thames River water provided most of the alkali for absorption, and about 20% was made up from lime addition. The process operated in an open-loop manner, returning spent reagent to the Thames. 

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