I am utilizing the PIDE block for autotuning with my Logix controller. While I have had success tuning for direct control variables such as pressure and flow, I have encountered difficulties with the level autotuner producing satisfactory results. I attempted to scale the Process Variable (PV) by a factor of 100 to generate larger changes for the algorithm to analyze, yet the outcomes were still unsatisfactory. Currently, my PIDE mode is set to reverse acting. Could anyone provide guidance on PIDE autotuning specifically for level control applications?
The concept of level control processes differs significantly from the processes that auto tune is intended to address, causing auto tune to struggle or even fail when applied to a level control system. In a flow control system, increasing the pump speed output from 50% to 60% leads to a rise in pump outlet pressure and flow. This results in a shift in equilibrium towards a new stable flow rate, with the system settling at around 120% of the initial flow rate. Stability is crucial in this type of system, which is what autotune algorithms are optimized for. On the other hand, when dealing with a level control system, increasing the pump speed output causes the level to rise due to a net accumulation of liquid in the tank. Unlike the flow control system, there is no equivalent mechanism to counteract the imbalance between inlet and outlet flows, leading to continuous rise in the level as long as the tank has capacity. Autotune algorithms are not tailored to address the challenges posed by such unstable systems.
I have never utilized the PIDE controller, let alone the autotune feature. However, it is crucial to recognize that, unless this system is unique, it will function as a Type 1, or single integrating, system for level control. Without informing the autotuner of this fact, it may struggle to generate an appropriate gain setting. It appears that I am a slow typer.
In analyzing control processes, it is crucial to recognize the distinction between level control systems and processes that can be optimized using auto-tuning algorithms. Auto-tune algorithms excel in stabilizing equilibrium in systems like flow controllers, where adjustments lead to predictable outcomes. These algorithms are adept at fine-tuning systems to find a stable equilibrium point. Contrastingly, when dealing with level control systems, the dynamics are different. Imagine a scenario where a level controller is on manual mode with the pump speed set at 50%, and the level is stable. Any increase in pump speed to 60% will lead to a continuous rise in the level due to the net accumulation of liquid in the tank. Unlike flow control systems, there is no equivalent mechanism to balance out the accumulation in a level control system, resulting in an unstable system. Therefore, it is essential to understand the specific characteristics of each type of control system when applying autotune algorithms. While autotune algorithms are effective in optimizing flow control systems, they are not suitable for stabilizing level control systems with inherent instability.
It seems I was mistaken about that, but now I know better.
While some may consider me traditional or old-fashioned, the PID block has been my go-to for achieving reliable level control for many years. Although I typically work with 1000 gallon tanks that don't require an extremely tight deadband, I have found success using the Ziegler-Nichols method for level tuning. For more information on this topic, check out this informative article: https://blog.opticontrols.com/archives/697.
Level control can indeed be tricky and each process has its own unique characteristics. Try reducing your controller gain; levels typically require a slower, more gentle control action. If your system includes disturbances or interactions between variables, you might want to consider feed-forward control. Your idea of scaling the PV was smart, although you actually might see better results on the opposite end of the spectrum, try minimizing PV changes instead. Also make sure to confirm your reverse acting mode is right for the process - in some cases, forward acting might be more appropriate. It's all about iterating and finding that sweet spot for your specific application. Best of luck!
It sounds like you've already tried a range of solutions, so I'm going to take a slightly different approach. Although this might sound counterintuitive, have you considered reducing the speed of your Integral and Derivative settings? Sometimes, when dealing with level control applications, a slower response can actually lead to more stability. This is because level control often involves larger volumes of substance and thus requires more time for changes to take effect. As a result, having high I and D values could lead to jittery control. Just a reminder, you need to adapt your gain accordingly to compensate for the slower action. Try this out and let us know how it goes.
When tuning the level control with PIDE in Logix controller, it's crucial to remember that factors such as dead time, response time, and most importantly, the size or capacity of the tank relative to the flow rate can greatly influence your tuning parameters. This might be why the scaling of PV didn't yield satisfactory results. For larger tanks with slower flow rates, you may require a more aggressive tune. Alternatively, with smaller tanks and fast flow rates, a more conservative approach might be needed. Also, you could try setting your PIDE mode to direct acting, as reverse acting can sometimes yield unstable results with level control applications. Lastly, don't forget that autotuning is just a starting point - you may need to manually adjust the tuning parameters in order to achieve optimal results.
One aspect you might consider is the inherent time delay that often accompanies level control, where changes in input do not instantaneously alter the level measurement. Typically, this delay can pose challenges for autotuners and could be why you're seeing unsatisfactory results. You might want to manually tune your controller, beginning with a very small proportional gain and then gradually increasing until you start to notice a stable oscillation. At that point, you can apply Ziegler-Nichols or other traditional tuning methods. Remember to keep your expectations realistic, as level control almost always involves compensating for changes over an extended period.
✅ Work Order Management
✅ Asset Tracking
✅ Preventive Maintenance
✅ Inspection Report
We have received your information. We will share Schedule Demo details on your Mail Id.
Answer: - To improve autotuning results for level control applications using the PIDE block, you can try adjusting the scaling of the Process Variable (PV) to generate larger changes for the algorithm to analyze. Additionally, consider the PIDE mode setting, ensuring it is appropriate for your system.
Answer: - The autotuning results may be unsatisfactory for level control due to the specific dynamics and characteristics of the level control application. It may require different tuning parameters or methods compared to pressure and flow control.
Answer: - The PIDE mode setting, whether direct acting or reverse acting, can have a significant impact on the autotuning process for level control applications. Make sure the mode setting is compatible with the behavior of your system to achieve satisfactory results.
Answer: - When autotuning for level control applications with the PIDE block, consider scaling the PV appropriately, adjusting tuning parameters based on the dynamics of the system, and ensuring the PIDE mode setting aligns with the control requirements of the application. Experiment with different settings to find the optimal configuration for your specific
Join hundreds of satisfied customers who have transformed their maintenance processes.
Sign up today and start optimizing your workflow.