Amazing New Transfer Function System Identification using PITOPS for PID Tuning and MPC Model Improvement

PiControl Solutions LLC PID tuning technology in PITOPS software is able to work with data considered bad, poor data quality, oscillating or closed loop with PID controllers in auto or cascade modes.

Most if not all of the conventional tools will quickly label such data as bad data and unusable. But PITOPS technology is able to use such data and is able to extract the disturbances and isolate the true relationship between the manipulated variable (MV) and the controlled variable (CV).

The amazing part of PITOPS technology is that the importing of the process data and completion of successful system identification takes literally less than 5 minutes. You will not get frustrated with error messages like what you may have seen from other technologies from other companies that will show message – “data quality poor”, “data contaminated or unusable”, “need more excitation or bigger step tests” or some cryptic OPC or systems related error messages that need reconfiguration, or uninstalling and reinstalling when you can’t figure out what the problem is.

With PiControl PITOPS software for PID tuning optimization and MPC model improvement, you will not need to write any “.M files” code like in MATLAB or any kind of Python code or C/C++ code but you can just take data from your plant and be able to successfully come up with amazing transfer function parameters that you can use for PID tuning, APC Advanced Process Control or improving MPC Model Predictive Control Models.

With PITOPS, slave PID controller can be in even Cascade mode not just Auto mode. The ability to use data with slave PIDs in Cascade mode is considered as “magic” even by skilled, experienced and highly qualified industrial process control advanced researchers and even ivy-league process control college professors.

PiControl PITOPS technology for PID tuning optimization and MPC models does not use ARMAX autoregressive moving average with exogenous inputs algorithm, nor partial least squares/Box Jenkins algorithm like other companies, does not use matrix algebra like Aspen DMC but uses totally different optimization technology that is behind the successful results where conventional tools and techniques fail.

We can do a free proof-of-concept POC project with you to show you this amazing new technology from PiControl Solutions LLC.