Model Predictive Control

Training Course

This process control training course teaches on the use of model predictive control (MPC) technology, staring from fundamentals: the history behind MPC, the need for MPC, when MPC is superior to other technology.

Training course description:

This process control training course teaches on the use of model predictive control (MPC) technology, staring from fundamentals: the history behind MPC, the need for MPC, when MPC is superior to other technology. 

This process control training course covers how to conduct open and closed loop step tests and identify true and accurate MPC models. How to design and build the MPC controller and how to do start-up and commissioning of MPC technology. 

This process control training course also covers MPC technology maintenance and how to modify and improve MPC models.  

The good prerequisites for this model predictive control training course are: 

Learning outcomes:

Students get a chance to learn how to: 

  • be skilled to design, maintain and troubleshoot MPC controllers. 
  • use modern closed-loop dynamics identification technology to improve MPC models. 
  • be skilled to observe plant trends and troubleshoot the MPC controller.

Audience:

Process control engineers, Advanced process control engineers, Instrument engineers, DCS / PLC technicians, Managers and Supervisors.

Duration:

Classroom training course: 3 Days (8-10 hours per day)

Online / Remote training course: 24 hours online  

Online video training course: 21 hours online

Training course program:

1st day:

  • Model predictive control (MPC) background 

  • Benefits of model predictive control (MPC)

  • Industrial use of model predictive control (MPC) technology

  • Alternate advanced process control (APC) technology

  • Model predictive control (MPC) software overview 

  • Model predictive control (MPC) modules and design procedure

  • Model predictive control (MPC) algorithm 

  • Model predictive control (MPC) step tests

  • Design of model predictive control (MPC) models

  • Harmful model predictive control (MPC) models 

  • Model predictive control (MPC) controller design and start-up

    2nd day:

  • Linear programming (LP)

  • Sequential quadratic programming (SQP) 

  • Linear programming (LP) costs and stable solution

  • Model predictive control (MPC) optimizer 

  • Model predictive control (MPC) controller maintenance

  • How to reduce/eliminate cycling and instability in MPC

  • Prediction error feedforward

  • Adaptive gains and nonlinear control challenges 

  • Advanced model predictive control (MPC) tips

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