Model Predictive Control Toolbox
Design and simulate model predictive controllers
Model Predictive Control Toolbox™ provides functions, an app, and Simulink® blocks for systematically analyzing, designing, and tuning model predictive controllers. You can set and modify the predictive model, control and prediction horizons, input and output constraints, and weights. The toolbox enables you to diagnose issues that could lead to run-time failures and provides advice on changing weights and constraints to improve performance and robustness. By running different scenarios in linear and nonlinear simulations, you can evaluate controller performance. You can adjust controller performance as it runs by tuning weights and varying constraints. For rapid prototyping and embedded system design, the toolbox supports C-code generation.
From Arkadiy Turevskiy, Model Predictive Control Toolbox Technical Expert