A controller seeks to maintain the measured process variable (PV) at set point (SP) in spite of unplanned and unmeasured disturbances. Since e(t) = SP — PV, this is equivalent to saying that a controller seeks to maintain controller error, e(t), equal to zero.
Processes with streams comprised of gases, liquids, powders, slurries and melts tend to exhibit variations in behavior as operating level changes. This, in fact, is the very nature of a nonlinear process. For this reason, our recipe for controller design and tuning begins by specifying our design level of operation.
Quantifying Dynamic Process Behavior Step 3 of the PID controller design and tuning recipe is to approximate process bump test data by fitting it with a first order plus dead time (FOPDT) dynamic model. Data from a proper bump test is rich in dynamic information that is characteristic of our controller output (CO) to measured […]
The control objective of the jacketed reactor case study, shown below and discussed in detailed in this article, is disturbance rejection. More specifically, we seek a controller design that will minimize the impact on reactor operation when the temperature of the liquid entering the cooling jacket changes.
Like the heat exchanger and gravity drained tanks case studies, the jacketed stirred reactor is a self regulating processes. That is, the measured process variable (PV) naturally seeks a steady operating level if the controller output (CO) and major disturbance (D) are held constant for a sufficient length of time.
We have investigated a graphical analysis method for fitting a first order plus dead time (FOPDT) dynamic model to step test data for both the heat exchanger and the gravity drained tanks processes in previous articles. Describing process behavior with an approximating FOPDT dynamic model is the third step of our controller design and tuning […]
We have explored the manual mode (open loop) operation and behavior of the gravity drained tanks process and have worked through the first two steps of the controller design and tuning recipe. As those articles discuss: ▪ Our measured process variable, PV, is liquid level in the lower tank, ▪ The set point, SP, is […]
We introduced the gravity drained tanks process in a previous article and established that it displays a self regulating behavior. We also learned that it exhibits a nonlinear behavior, though to a lesser degree than that of the heat exchanger. Our control objective is to maintain liquid level in the lower tank at set point […]
Self Regulating vs Integrating Process Behavior This case study considers the control of liquid level in a gravity drained tanks process. Like the heat exchanger, the gravity drained tanks displays a typical self regulating process behavior. That is, the measured process variable (PV) naturally seeks a steady operating level if the controller output (CO) and […]
Over a series of articles, we generated step test data from a heat exchanger process simulation and then explored details of how to perform a graphical analysis of the plot data to compute values for a first order plus dead time (FOPDT) dynamic model. The claim has been that the parameters from this FOPDT model […]