Model Predictive Control by Using Excel

Model Predictive Control (MPC) is a tool to control a system with multiple inputs and outputs. Nowadays, many researchers, managers and engineers are applying this tool in different fields such as financial management, strategic management and also many engineering fields.

Here I found two good links on Internet which give us some interesting examples and simulation 

models useful for piping engineers as follows:

https://controls.engin.umich.edu/wiki/index.php/MPC

 Model Predictive Control: Title

 Video lecture available for this section!  Note:

Bradley Anderson, Aaron Bennick, Michael Salciccioli: Authors

 sSarah Hebert, Valerie Lee, Matthew Morabito, Jamie Polan

Date Presented: 11/7/06; Revised: 10/30/07

Implementing MPC using Excel

In MPC, values of the control variables will be optimized for a given time interval in order to best tell the system how it should act. The control variables will be optimized by optimizing some characteristic. Usually, this characteristic is simply the least squared error between an actual state and a "set" or desired state. This can easily be done using the Solver tool in Excel.

You can find a good example of MPC and download excel spreadsheet for more practice on the above link.

Simulation of a Model Predictive Controller

You can also find an example on below link which gives us an application to simulate a Model Predictive Controller (MPC) for a single input, single output (SISO) first order with time delay process. You can download excel spread sheet for more practice.

http://www.engineers-excel.com/Apps/MPC/Description.htm

Of course, always the assumptions and arrangement of components model have very important role to reach good predictions and valid results.