A practical multiple model adaptive strategy for multivariable model predictive control

摘要

Model predictive control (MPC) has become the leading form of advanced multivariable control in the chemical process industry. The objective of this work is to introduce a multiple model adaptive control strategy for multivariable dynamic matrix control (DMC). The novelty of the strategy lies in several subtle but significant details. One contribution is that the method combines the output of multiple linear DMC controllers, each with their own step response model describing process dynamics at a specific level of operation. The final output forwarded to the controller is an interpolation of the individual controller outputs weighted based on the current value of the measured process variable. Another contribution is that the approach does not introduce additional computational complexity, but rather, relies on traditional DMC design methods. This makes it readily available to the industrial practitioner.