Model Predictive Control Design Parameters | Understanding MPC, Part 3

This video provides recommendations for choosing the controller sample time, prediction and control horizons, and constraints and weights. To successfully control a system using an MPC controller, you need to carefully select its design parameters.

Watch all of the videos in this series about Understanding Model Predictive Control:    • Understanding Model Predictive Control  

Download this hands-on MPC virtual lab to practice design of model predictive controllers for an autonomous vehicle steering system: https://bit.ly/MPC-virtual-lab

Learn how model predictive control (MPC) works:
Model Predictive Control Toolbox: http://bit.ly/2xgwWvN
What Is Model Predictive Control Toolbox?: http://bit.ly/2xfEe2M
Design Controller Using MPC Designer: http://bit.ly/2GI2lhV

Related Resources:
How to Design Model Predictive Controllers: http://bit.ly/2M0BOd9
Choose Sample Time and Horizons: https://bit.ly/3QPS5GL
Specify Constraints: https://bit.ly/3E5AXoy
Tune Weights: http://bit.ly/2LXl72r
How to Design an MPC Controller with Simulink and Model Predictive Control Toolbox: http://bit.ly/2Gvv0qe
Adaptive MPC Design with Simulink and Model Predictive Control Toolbox: http://bit.ly/2GsL5Nu

Watch more MATLAB Tech Talks: http://bit.ly/2rTc8Yp
Get a free MATLAB Trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See What's New in MATLAB and Simulink: https://goo.gl/pgGtod

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