Model Predictive Control Toolbox provides functions, an app, and Simulink blocks for designing and simulating model predictive controllers (MPCs). The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. By running closed-loop simulations, you can evaluate controller performance. You can adjust the behavior of the controller by varying its weights and constraints at run time. To control a nonlinear plant, you can implement adaptive and gain-scheduled MPCs. For applications with fast sample rates, you can generate an explicit model predictive controller from a regular controller or implement an approximate solution. For rapid prototyping and embedded system implementation, the toolbox supports automatic C-code and Structured Text generation. The most important content that this book provides are the following: -MPC Modeling -Plant Model -Disturbance Model -Measurement Noise Model -Signal Types, Inputs and Outputs -Construct Linear Time Invariant (LTI) Models -Transfer Function Models -Zero/Pole/Gain Models -State-Space Models -LTI Object Properties -LTI Model Characteristics -Specify Multi-Input Multi-Output Plants -CSTR Model -Linearize Simulink Models -Linearization Using MATLAB Code -Linearization Using Linear Analysis Tool in Simulink Control Design -Linearize Simulink Models Using MPC Designer -Define MPC Structure By Linearization -Linearize Model -Specifying Operating Points -Connect Measured Disturbances for Linearization -Identify Plant from Data -Identify Plant from Data at the Command Line -Working with Impulse-Response Models -Design MPC Controller for Identified Plant Model -Design Controller for Identified Plant Using Apps -Design Controller for Identified Plant at the Command Line -Configure Noise Channels as Unmeasured Disturbances -Design Controller Using MPC Designer -Test Controller Robustness -Design MPC Controller for Plant with Delays -Design MPC Controller for Nonsquare Plant -Design MPC Controller at the Command Line -Simulate Controller with Nonlinear Plant -Nonlinear CSTR Application -Example Code for Successive Linearization -CSTR Results and Discussion -Compute Steady-State Gain -Extract Controller -Signal Previewing -Update Constraints at Run Time -Update Bounds on Input and Output Signals at Run Time -Update Custom Linear Constraints at Run Time -Tune Weights at Run Time -Designing and Testing Controllers in Simulink -Design MPC Controller in Simulink -Test an Existing Controller