# MPC控制器

## Generals

• MPC: regulatory controls using an explicit dynamic model of the response of process variables to changes in manipulated variables.
• $obj = min(\sum (y - y_{trajectory})^2)$
• basic version uses linear model. Can also be empirical model.

• long time constants, substaintial time delays, inverse response, etc;
• multiple variables
• has constraints over process variables
• General characteristcs:

• targets (set points) selected by real-time optimization software based on current operating and economic conditions
• minimize square of deviations between predicted future outputs and specific reference trajectory to new targets
• handles MIMO control problems
• can include equality and inequality constraints on controlled and manipulated variables
• solves a nonlinear programming problem at each sampling instant
• disturbance is estimated by comparing the actual controlled variable with the model prediction
• usually implements the first move out of $M$ calculated moves
• MPC target trajectories

• Types:
• Funnel Trajectory