Model Predictive Control Toolbox™ provides functions, an app, and Simulink® blocks for systematically analyzing, designing, and simulating model predictive controllers. 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 controller performance 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.
Design and simulation of model predictive controllers in MATLAB® and Simulink
Customization of constraints and weights with advisory tools for improved performance and robustness
Adaptive MPC control through run-time changes to internal plant model
Explicit MPC control for applications with fast sample times using pre-computed solutions
Control of plants over a wide range of operating conditions by switching between multiple model predictive controllers
Specialized model predictive control quadratic programming (QP) solver optimized for speed, efficiency, and robustness
Support for C-code generation with Simulink Coder™ and IEC 61131-3 Structured Text generation with Simulink PLC Coder™