Model Predictive Controller (MPC) Maintenance and Improvement Services from PiControl Solutions

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[email protected], Tel: (832) 495 6436

Improve your model predictive controller (MPC) performance using PiControl Solutions software and technology.  PiControl offers remote model predictive controller (MPC) maintenance consulting and support.  Any model predictive controller (MPC) software – DMC (Dynamic Matrix Control), RMPCT (Robust Model Predictive Control Technology), Predict Pro, Connoisseur, or any other can be improved.  PiControl software is called COLUMBO – closed loop universal multivariable optimizer.  COLUMBO reads Excel data files containing MV, CV and FF data from the model predictive controller (MPC).  Its powerful optimizer then refits existing MPC models and improves MPC models accuracy thereby reducing prediction errors.  A fast, powerful, novel, revolutionary method of improving any MPC models using a totally new methodology not available in any other product.

Model predictive controller (MPC) performance may be poor because of any of the following:

1) Incorrect MPC dynamic models.

2) Poor selection of MV and CV variables inside of model predictive controller (MPC).

3) Poor PID tuning for slave PIDs connected to the model predictive controller (MPC).

4) Certain CVs and MVs in current model predictive controller (MPC) that need to be relocated to DCS-based APC (advanced process control).

5) Judicious selection and deletion of dynamic MPC models.

6) Combining process engineering knowledge to improve model predictive controller (MPC) performance.

PiControl can help you in checking your model predictive controller (MPC) and fixing all six above listed opportunities.

COLUMBO just reads offline Excel files, does not need to connect to the Level 3 process control network – so there are no cyber security concerns!

COLUMBO can read Excel files with MV, CV and FF (manipulated variable, controlled variable and feedforward variable) data with the model predictive controller (MPC)ON (active and in closed-loop mode).  With the normal changes in CV targets limits (setpoints) or the normal changes in DVs (disturbance variables), COLUMBO optimizer can determine new and improved models with superimposing new intrusive step tests on the setpoints of the slave PIDs.  Not needing new intrusive step tests prevents plant perturbations and disturbances and reduces stress and headaches for the control room operator.

PiControl can help you improve your model predictive controller (MPC) remotely – no travel costs, all work can be done safely and remotely.  Contact PiControl at [email protected] and let us help you improve your model predictive controller (MPC) performance today.  Increase plant profits and benefits using COLUMBO software from PiControl.