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MPC控制器

Generals

  • MPC: regulatory controls using an explicit dynamic model of the response of process variables to changes in manipulated variables.
  • basic version uses linear model. Can also be empirical model.
  • advantages over PID:

    • 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 calculated moves
  • MPC target trajectories

    • Types:
      • Funnel Trajectory
      • Pure dead-band
      • Referecen Trajectory
    • Near-term vs. long-term objectives
    • Response Target
    • Response Speed
  • Quadratic objective

Details

  • Impulse and step response models and the prediction equation
  • Use of state estimation
  • Optimization
  • Infinite-horizon MPC and stability
  • Use of nonlinear models