Model Predictive Control Toolbox™ provides functions, an app, and Simulink® blocks for systematically analyzing, designing, and simulating model predictive controllers (MPCs). You can specify plant and disturbance models, horizons, constraints, and weights. The toolbox enables you to diagnose issues that could lead to run-time failures and provides advice on tuning weights to improve performance and robustness. By running different scenarios in linear and nonlinear simulations, you can evaluate controller performance.
You can adjust the performance of the controller as it runs by tuning weights and varying constraints. You can implement adaptive model predictive controllers by updating the plant model at run time. For applications with fast sample times, you can develop explicit model predictive controllers. For rapid prototyping and embedded system design, the toolbox supports C-code and IEC 61131-3 Structured Text generation.
Optimize closed-loop system performance of MIMO plants subject to input and output constraints.Learn more
Optimize controller performance by adjusting controller constraints and weights, as well as the models and gains used in state estimation.Learn more
Control a nonlinear Simulink plant model over a wide range of operating conditions.Learn more
Discover more about Model Predictive Control Toolbox by exploring these resources.
Explore documentation for Model Predictive Control Toolbox functions and features, including release notes and examples.
Browse the list of available Model Predictive Control Toolbox functions.
View a Simulink library of blocks that Model Predictive Control Toolbox supports.
View system requirements for the latest release of Model Predictive Control Toolbox.
View articles that demonstrate technical advantages of using Model Predictive Control Toolbox.
Read how Model Predictive Control Toolbox is accelerating research and development in your industry.
Find answers to questions and explore troubleshooting resources.
Model Predictive Control Toolbox apps enable you to quickly access common tasks through an interactive interface.
Use Model Predictive Control Toolbox to solve scientific and engineering challenges: