Optimal Control with Model Predictive Control Toolbox
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This one-day course provides a comprehensive introduction to the Model Predictive Control Toolbox™.
Topics include:
- Linear model predictive control (MPC)
- Adaptive MPC
- Multi-stage nonlinear MPC
- Deployment
Day 1 of 1
System Modeling Techniques
Objective: Create system models for use with MPC.
- Model representations overview
- Linearization
- System analysis
Linear MPC
Objective: Interactively define a linear implicit MPC using the MPC Designer app.
- Elements of traditional MPC
- Preparing a model for MPC
- Designing and tuning a linear MPC with the MPC Designer app
Adaptive MPC
Objective: Design an adaptive MPC for nonlinear plants with varying dynamics.
- Operating point selection
- Adaptive MPC block
- State estimation
Nonlinear MPC
Objective: Design a nonlinear MPC using nonlinear prediction models, cost functions, and constraints for nonlinear plants.
- Understand the use cases for nonlinear MPC
- Build a nonlinear MPC object
- Understand the state, cost and constraint functions and their Jacobians
- Implement nonlinear MPC for a nonlinear control problem
