Posts Tagged ‘Process Variable’
Pulse is Okay, but Doublet is Better
The Pulse and Doublet tests both allow practitioners to observe the process moving in opposite directions, but which is better?
Read MoreWhat is Process Gain? Why is Process Gain important when tuning Processes?
Professionals who tune PID controllers using manual methods tend to agree that understanding the Process Gain of their system is of the up-most importance. Among industry practitioners the Process Gain is often referred to as the “how far” or even the “sensitivity” variable and yet these descriptions can be rather vague to beginners.
Read MoreWhat Value is Hidden in a Plant’s Process Data
While a typical Distributed Control System (DCS) keeps a watchful eye on production and scheduling there are other important details that a DCS simply overlooks. To be clear, a DCS consumes process data in order to measure and regulate the flow of material through a plant. It interprets sensor data and orchestrates adjustments to Final Control Elements in order to maintain Set Points.
Read MorePros and Cons of Higher Order Models
Modeling is a time-tested approach for decoding a process’ dynamic behavior. By understanding how a process responds to change it’s possible to apply an appropriate and timely counter measure. Two common applications of modeling are 1) PID controller tuning, and 2) process simulation.
Read MoreHow to Perform a Step Test
Tuning PID controllers is a multi-step process. While it is important to understand each step in the process, performing the bump test and collecting dynamic data is the most crucial step that generally dictates the outcome. This post delves into one particular type of test – the Step Test – before introducing other tests commonly used in PID controller tuning.
Read MoreData Collection Speed is Key to the Accurate Interpretation of Process Dynamics
If you’re old enough to remember silent movies, then you know what it’s like to see the characters seemingly jiggle around the screen. Black spots would randomly appear as the story was told with the help of subtitles. Spots and subtitles aside, these movies appeared jittery due to their slow speed. The slow frame rate – a precursor of data collection speed – resulted in visual gaps.
Read MoreHow Can I Correct for Noise Using External Filters?
Choices, choices. In the realm of process control practitioners are regularly forced to choose between competing options. Consider a PID control loop: Should it be tuned for faster disturbance rejection or tighter Set Point tracking? Should the Derivative Term be used or does the PI configuration provide a sufficiently fast Settling Time? And the choices go on and on. In that sense there are multiple choices for filtering noise too – options that provide very different benefits. Fortunately when it comes to filtering for Signal Noise the choice is typically clear.
Read MoreHow Can I Correct for Noise Using Internal Filters?
Noise is inevitable. To one degree or another it’s evident in the data of most every production process. Sure it can be absent in academic settings and similar lab environments where simulations often generate sanitized data. However, in the real world of industrial manufacturing noise is a factor that cannot be avoided. Failing to account for or manage noise can be a recipe for – well – failure.
Read MoreWhat is the Purpose of a PID Controller’s Integral Term? Why is PI Control So Widely Used in Industry?
In the realm of process control it makes complete sense that the primary goal is – you guessed it – to control the process. For decades the PID controller has proven a reliable tool for fulfilling that objective. Even so, there are various forms of the controller that can be used and each has its unique performance attributes. In spite of the added complexity associated with the Integral Term the PI controller is the form most widely used in industry.
Read MoreModel-Based Tuning Methods For PID Controllers
The manner in which a measured process variable responds over time to changes in the controller output signal is fundamental to the design and tuning of a PID controller.
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