In this screencast we will discuss the concept of cascade control, how it's implemented, and discuss the block diagram for cascade control. So before we do this we have to think about why we would want cascade control. The majority of all processes that are being controlled take advantage of feedback only control because of the numerous advantages that it provides, its robustness, its ability to measure the controlled variable and act, it's ease of implementation, etc. However, there are a few major drawbacks to feedback control which makes it impractical for particular types of purposes. The first is the fact that perfect control cannot occur. This may or may not be of huge concern, but it does work out more conveniently if you can develop a process where for a particular disturbance it can handle the disturbance such that the controlled variable is not changed.
The second issues is that predictive control does not occur with a feedback only scheme. Why? Because remember what feedback control does. Feedback control only deals with measurements of the controlled variable, so therefore even if we knew something was going to happen, like we knew that there was going to be a flow rate change somewhere in the process, a temperature change, a pressure change, something along those lines. The feedback control scheme will not be able to handle that until there is a deviation in the value of the controlled variable. So therefore for processes which have heavy disturbances having a feedback only scheme may have some problems, and related to that is for processes which are very slow or have large dead times they don't necessarily handle disturbances well because of that slow time to respond. So a disturbance will happen, but because of the large dead time of the process, or large tau value, the time constant of the process, it will not be able to handle disturbances in a very efficient, quick manner, leaving the process away from its steady state for a lengthy period of time. So cascade control cannot provide perfect control, we'll discuss why a little bit later on, however it can help in both predictive control and speeding up the process.
Both those two are directly related to each other. So cascade control can best be approximated as the idea of feedback control loops in series, and to exemplify this we have a jacket reactor on the diagram, where the desired variable to control here is the temperature inside the reactor, so this is our controlled variable, and the reason why you would want to control temperature in a reactor would be that it can be useful to prevent runaway reactions, it can also be a nice way to, based on doing a mass balance on the system, know what your products are going to be, so therefore to get your system at its desired output you have to set a particular temperature, because temperature dictates reaction rate. So in this control scheme the manipulated variable is going to be the flow rate of coolant to the system.
Obviously there is a whole host of other ways in which this could be manipulated, but for the sake of what we're doing here it's the flow rate of the coolant. The temperature controller does not directly connect to the valve, there is a second layer here where the temperature controller sends its signal to a flow controller, and then the flow controller is also taking in information from the flow rate of the coolant, so what's measuring here is the coolant flow rate, and the flow controller is taking that information in addition to the information from the temperature controller in order to adjust the valve. So the temperature controller is represented as the primary controller.The primary controller in a cascade control scheme will always be the controller that corresponds to the controlled variable, in this case the reactor temperature, and the flow controller is the secondary controller, primary, secondary, there can be more than two layers of cascade control, so there can be ternary, quaternary, etc., whatever is lowest in the hierarchy is the one that will directly control the valve. So some important information about the secondary controller, there are two things that need to be the case in order for this to be a useful cascade control scheme. The first is the variable must fluctuate, and it must be a non-negligible fluctuation. Why? Because if the variable doesn't fluctuate then the extra information being provided to the process is not useful. Additionally if the fluctuations are relatively small in scale, small is in the eye of the beholder, then again it really isn't going to help improve this process.
The second part is remember that the whole idea of cascade control, if we look at the disadvantages of feedback control, is to speed up the process response, so therefore the secondary control loop must have a faster response than the primary loop. A rule of thumb here is about three times faster, where this three times can come from doing some time analysis of the tau value, the time constant. If it's a little less than three times what the issue is the fact that you now have this counter balancing between yes, you're quickening your response, but you've now also introduced new equipment which can have fluctuations, or which can break, so therefore in terms of what is the net gain to the controls overall it may not be as much as you'd think. To go back to the issue of why perfect control cannot occur here, the reason why perfect control cannot occur here is that there is still a connection here to the primary variables.
So in other words the secondary variables decision making process is based on what is going on with the primary variable, so therefore it helps mitigate the idea of the possibility of perfect control. So what we'll do here is kind of talk about the loop in a bit more detail. If we see a deviation to the temperature, the controlled variable, the temperature inside the reactor, the temperature controller is going to send a signal to the flow controller saying I need more or less coolant. So in other words what this is really doing is this signal here, sent from the temperature controller to the flow controller, is setting a new set point for the secondary controller. So with this new set point the secondary controller can then take what the new value should be in order to get the desired temperature, compare it to what the flow rate of the coolant actually is, take those two pieces of information together, and adjust the valve.
Additionally what this can also do is handle adjustments in the flow transmitter, the flow of the coolant, and make those adjustments even if the temperature has not changed, again this is why the response is quicker than it would have been originally if we just had a pure feedback scheme where the temperature controller wasn't directly connected to the valve. So the question now to ask is how does this all get represented on a block diagram. So to show this we'll start with our output variable, and we'll use the example of the reactor I have here, so therefore the output here would be the temperature of the reactor. So we'll just follow the six steps here, where again this does have a large root in feedback control, so therefore temperature of the reactor will then go to the sensor transmitter, the temperature transmitter, from the temperature transmitter it will go to the controller. Remember the fact that the controller has to take in an error, so therefore we need to compare it to the set point of the reactor, multiply it by Km in order to get it into appropriate units, and from there we'll connect it to the controller, and in this case if we follow the arrows here we're talking here about the temperature controller. If we follow the arrows further the temperature controller then sends its information to the flow controller, and we note the fact that the flow controller takes in two signals, so we're going to put a summing point here because we know we're going to need this, so from the flow controller we then send the signal to the valve, and then from the valve we then have our process, which is the reactor, so for our case here what comes out of the valve is the flow rate of the coolant, so because that comes as the flow rate of the coolant we'll draw our cascade part here. This would represent the flow transmitter, and we have completed our loop, so therefore this shows how cascade control represents a nested feedback loop.
Because of this nestedness what this also means is that the secondary loop impacts the primary loop, and this is most notable with respect to tuning, where in order to properly tune this control scheme we also have to take into account the secondary control loop. Generally when tuning you tune from the inside out, so therefore in this case we would tune by starting with the secondary loop, then the primary loop. So for the sake of what we're talking about here this would be the flow loop first, then the temperature loop. The stability of the process can be greatly influenced by how the secondary flow loop has been tuned. So in this screencast we discussed the ideas of cascade control, provided an example, and showed how it's implemented, and also discussed control loops set up from a sample cascade system.
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