Posts Tagged ‘Process Variable’
Modeling Non-Steady State Data for PID Controller Tuning in a Cogeneration Power Plant
A 25 MW combined-cycle cogeneration plant at the University of Connecticut supplies electricity to the entire UConn campus with three natural gas combustion turbine generators and one high pressure steam turbine generator.
Read MoreWhat is Feed-Forward Control?
In a previous post cascade control was introduced as an effective means of limiting the lag between an upset and the associated PID control loop’s correction. As practitioners know: The longer the delay in responding, the larger the negative impact on a process. Like cascade, Feed-Forward enables the process to preemptively adjust for and counteract the effects of upstream disturbances.
Read MoreDefault Out-of-the-Box Settings Prevent the PID Controller from Achieving its Goal
Tuning a PID controller doesn’t have to be hard. Whether a practitioner chooses to tune control loops manually or with the help of software, the procedure is relatively straight forward and can produce highly effective results. It can be argued that using software is faster and provides more optimal results than manual tuning, but that’s an argument that largely depends on the economic importance of the PID control loop in question. In the end, the goal is the same: To tune for improved control loop performance.
Read MoreHow Does the Derivative Term Affect PID Controller Performance?
Derivative is the third term within the PID. In mathematical terms the word derivative is defined as the slope of a curve. Seen in the context of strip chart data derivative represents the rate of change in error – the difference between the Process Variable (PV) and Set Point (SP). Like the proportional and integral terms within a PID controller, the derivative term seeks to correct for error. Valuable as the third term can be in maintaining effective control, experience suggests that appropriate uses of derivative are not entirely clear.
Read MoreHow Do I Calculate Dead-Time?
Adults can learn a thing or two from children. That’s especially true when it comes to matters of time. Whereas adults view it as fashionable to show up to a social event 15 or more minutes late, children can’t wait to go and be a part of the action. When at a theme park adults typically their time strolling from place to place while children know that each minute of delay can cost hours longer in line. Simply put: When it comes to time every second matters. That viewpoint seems highly relevant to process control, control loop tuning, and calculating Dead-Time. Dead-Time is generally the model parameter that’s easiest to calculate when tuning a PID controller.
Read MoreHow Do I Detect Valve Issues and Prevent Failures?
It’s generally known that the behavior of final control elements (FCEs) (valves, air handlers, etc.) change over time. Like most things the dynamics of FCEs are different from the time they’re first installed to the time they’re serviced and ultimately replaced. Sometimes the change in dynamic behavior is subtle. Other times the change is dramatic. Unfortunately that’s the nature of things, and that’s the primary reason why monitoring for valve issues is beneficial.
Read MoreWhat is the Process Time Constant? How Do I Calculate the Time Constant of A Process?
Party hosts often cringe when guests arrive early or late. Seemingly subtle shifts in timing can throw off planned details that are of importance to the host and utterly lost on guests. So too the timing of a PID control loop’s response is important. Premature or delayed responses negatively impact the controller’s performance. Previously the calculation of Process Gain – the “how far” variable – was covered. The Process Time Constant is equally important to process modeling and PID controller tuning. As with most things, timing is everything.
Read MoreHow Do I Calculate Gain? What Is the Difference Between Process Gain and Controller Gain?
Among practitioners who tune PID control loops manually most note their focus on calculating the Gain. Process Gain is a model parameter whereas Controller Gain is a tuning parameter. The former describes important aspects of a given process’ dynamic behavior. The later contributes to the PID controller’s responsiveness to disturbances.
Read MoreWhat Are the Pros and Cons of the Step Test?
Face it, more often than not tuning a PID controller is usually easier when software is applied. While not all products are created equal, the modeling capabilities within most commercial controller tuning software products can account for dynamics that are often overlooked by the human eye. Noisy and oscillatory data can thwart even the most experienced among us. So what should a practitioner do when the use of tuning software isn’t an option? The answer: Perform a step test.
Read MoreHow Do I Tune a Level Controller?
Level controllers present challenges that are different from others. Although their presence is significant they lag behind Flow controllers in their overall share of the typical production facility’s process control landscape. Unlike other processes such as Temperature, Pressure and Flow, Level control loops demonstrate different dynamics, they don’t play by the same rules as the non-integrating (also known as self-regulating) types. And although best-practices for modeling and tuning Level loops are similar they involve nuances that can hamper a less experienced practitioner.
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