Hans-Petter Halvorsen

Model predictive control (MPC) is an advanced method of process control that has been in use in the process industries since the 1980s. Model Predictive Control (MPC) is a multivariable control algorithm. Model predictive controllers rely on dynamic models of the process.

Traditional feedback controllers operate by adjusting control action in response to a change in the output set-point of a system. Model predictive control (MPC) is a technique that focuses on constructing controllers that can adjust the control action before a change in the output set-point actually occurs. This predictive ability, when combined with traditional feedback operation, enables a controller to make adjustments that are smoother and closer to the optimal control action values.

Model Predictive Control in LabVIEW:

Model Predictive Control in LabVIEW - Here we use LabVIEW for Model Predictive Control (MPC) Applications.

In this application we will Control a Level Tank System using different control strategies:

- PID
- Use Kalman Filter for Estimation of Unknown Process Variables/Measurements
- PID + Feedforward (with help of Kalman Filter)
- MPC (+ Kalman Filter)

We will not go in depth of the theory/mathematics (but the basics will be presented), but focus on the practical implementation in LabVIEW.

Videos:

LabVIEW PID + Kalman Filter + MPC - Part 1 - YouTube Video

LabVIEW PID + Kalman Filter + MPC - Part 2 - YouTube Video

LabVIEW PID + Kalman Filter + MPC - Part 3 - YouTube Video

LabVIEW PID + Kalman Filter + MPC - Part 4 - YouTube Video

LabVIEW PID + Kalman Filter + MPC - Part 5 - YouTube Video

Resources:

Learn Basic LabVIEW Programming

LabVIEW programming and Training

LabVIEW Videos withn different Applications and Areas

LabVIEW Tutorials

Programming Resources

Automation and Control Resources