May 2010

In this issue

• Trick
• Courses
• Articles
  

Trick

Advanced Controllers

Model Predictive Control, or MPC, is an advanced method of process control that relies on dynamic models of the process.

The applied models are determined to depict the behavior of complex dynamical systems. The models are used to predict the behavior of process characteristics such as quality and limits. MPC manipulates setpoints of regulatory controllers that govern valve movement.

The model predictive controller uses the models and current plant measurements to calculate future moves in the setpoints that will result in operation that honors all variable constraints.

MPC calculates each move solving equations to minimize a cost function where each characteristic has a weight and without violating constraints.

MPC can be implemented in some DCSs or using a special program specially designed.

 

To optimize MPC controllers, one has to model the processes, adjust cost functions and constraints.

Optimization is a very good investment! Usually, within few weeks, money invested is recovered.Do not hesitate to contact us; we can help you.

Contact us!

Courses

See our calendar: we offer workshops on control strategies, performance supervision, advanced process control, alarm management, etc.

Next classes:

WS-100-2E
Workshop on PID Troubleshooting and Tuning, with Cascade and Feedforward

Atlanta GA,    May 4-5, 2010

To learn more

Articles

Two articles have been added to our  WEB site.

CLOSED LOOP TUNING VS OPEN LOOP TUNING-Tuning all your Loops While the Process is Running is Now Possible, PAPTAC 2010, Montreal, February 2 2010, by Michel Ruel

To learn more

Tracking performance after optimizing a deinked plant, PAPTAC 2010, Montreal, February 3 2010, by Michel Ruel

To learn more