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Tadpole is a completely new, breakthrough product to reliably detect oscillations in any process using PiControl’s proprietary TAD (True Amplitude Detection) algorithm invention. No other competitor has access to the TAD algorithm.
Tadpole is an online software product to reliably detect oscillations in important control loops in a chemical plant. Every plant has several control loops ranging from as few as ten in a small plant to hundreds in a large complex that are considered critical. Examples of such loops are reactor temperature, distillation temperature, product purity, surge calculation in compressor, certain important valve positions, motor amps or power and many others. Oscillation of these loops because of change in plant or process conditions or excitement caused by interacting external loops or disturbances can cause the entire process to start oscillating. This can result in lost production because of inability to operate closer to constraints and it can also impact product quality.
Tadpole provides an online window which can be displayed in the control room showing the oscillation status of all important tags. A quick glance at the screen and the engineer/operator is alerted on loops that are oscillating.
The field of online oscillation detection is still very much in its infancy. PiControl’s Tadpole will reliably and unfailingly determine instability and/or hunting as soon as it is mathematically possible. PiControl’s revolutionary TAD (true amplitude detection) software coupled with other iterative online algorithms process the data effectively and fast, and make it possible to reliably detect instability and oscillations like no other technique or software available in the market.
See Figure 1 for an illustration about the capability of Tadpole.
In case 1, amplitudes are growing, this is a sign of impending instability. In case 2, amplitudes are high but constant, rather large; this is a sign of hunting.
Cases 1 and 2 are easier to flag as a problem compared to case 3.
In case 3, there are small peaks and valleys all over, as is typical in a chemical plant signal. Some of the amplitudes are high, but might be passing (temporary). Some of the smaller ones may be real and important.
Most competitor products get confused by the squiggles in the data and can miss real oscillations or report false ones.
Tadpoles’s TAD algorithm guarantees correct identification of oscillations unfailingly, irrespective of the extent of data noise and data squiggles. Tadpole’s™ capability of identifying oscillations reliably irrespective of the nature of the fast noise, medium or slow process drift is totally unique and unmatched by any competitor product.
Tadpole also alerts if the control is sluggish (too slow).
Based on the oscillation and control status, Tadpole generates a status 1, 2, 3, 4 online alarm signal. The signal meaning is as follows:
Tadpole can be used to switch tuning automatically on critical tuning loops and also alarm operators, control engineers. Prior to Tadpole technology, detection of the problem could take much longer resulting in possible equipment shutdown, process problems and lost production or quality.
Model Predictive Controls (MPC) can have 10s or 100s of dynamic models. One or more could be wrong. Bad (wrong) Model Predictive Control (MPC) dynamic models produce a bias (model prediction error) between the predicted signal and measured signal coming from the sensor.
How to identify the bad (wrong) Model Predictive Control (MPC) models and how to generate correct models?
This has been a long challenging problem and a nightmare for the process control staff responsible for Model Predictive Control (MPC) quality and performance. Now COLUMBO offers a breakthrough, novel and state-of-the art solution like never before.
Tadpole can be made to run as fast as every 10 seconds, 1 minute, as slow as 30 minutes or even slower. The online run status screen for Tadpole is shown in Figure 2.
Tadpole analyzes the signal from historical data and then determines the true amplitudes. The true amplitudes from a real-plant data set is shown in Figure 3.
Loops that are oscillating (either unstable or hunting) are flagged. The spectrum distribution calculation is shown for all tags, as shown in Figure 4.
Figure 5 shows the online oscillation tuning display screen for customizing the oscillation detection. Some tags oscillate more than others and this might be natural and unavoidable. To avoid false positives and annoying false alerts, Tadpole allows tuning of each tag so that only the real oscillations are alerted.
Tadpole can be easily made to trigger adaptive control schemes and rule-base control schemes to:
PiControl provides free technical support for designing and implementing these adaptive schemes and controllers.
Tadpole is the first truly simple, powerful and practical adaptive control solution for the practical control room environment.
A) Moves are 1-2% of the3 current slave setpoints during model identification stage but could be 1-30% of the current slave setpoints with Model Predictive Control (MPC) running trying to provide control.
B) During model identification stage, only one MV is moved at a time followed by waiting time to try to see the new steady state. This is recommended by all Model Predictive Control (MPC) vendors as a good guideline to avoid correlation problems as if more than one MV (slave PID setpoint) is changed at the same time, then there is ambiguity and uncertainty regarding the impact of the multiple variables and subsequently dynamic models could be wrong due to correlations. However, when the Model Predictive Control (MPC) is running, the Model Predictive Control (MPC) moves various MVs (slave PID setpoints) simultaneously in order to keep the CVs at their targets.
How does COLUMBO work? What are details about the COLUMBO algorithm and internals? The COLUMBO algorithm is a PiControl invention and PiControl corporate intellectual property and cannot be disclosed in open literature. All that can be revealed is that COLUMBO tries to identify new models based on the measured data (CVs) and the MV trajectory calculated by the Model Predictive Control (MPC) system or the Advanced Process Control (APC) system. Internally, COLUMBO is equipped with a powerful and new optimizer designed for handling multiple inputs, both analog and digital subject to constraint limits and nonlinear math processing capabilities. Written in C++, COLUMBO code is super-fast and super-compact allowing the optimization calculations to complete and converge in an amazingly short time. See below an overview of how COLUMBO works:
For technical help and additional details on Columbo, please contact PiControl Solutions Company via email at info@PiControlSolutions.com