Abstract
An analytical model predictive control (MPC) tuning method for multivariable first-order plus fractional dead time systems is presented in this paper. First, the decoupling condition of the closed-loop system is derived, based on which the considered multivariable MPC tuning problem is simplified to a pole placement problem. Given such a simplification, an analytical tuning method guaranteeing the closed-loop stability as well as pre-specified time-domain performance is developed. Finally, simulation examples are provided to show the effectiveness of the proposed method.
Highlights
Model predictive control (MPC) is widely applied in various kinds of applications in different industrial areas like chemical, petrochemical, automotive, and aerospace [1,2,3]
As a large portion of the industrial processes controlled by MPC can be effectively modeled by first-order plus dead time (FOPDT) systems, we focus on MPC tuning for FOPDT systems in this work
In Bagheri and Khakisedigh [14], an analytical MPC tuning method is proposed for a single-input single-output (SISO) FOPDT model without active constraints
Summary
Model predictive control (MPC) is widely applied in various kinds of applications in different industrial areas like chemical, petrochemical, automotive, and aerospace [1,2,3]. In Bagheri and Khakisedigh [14], an analytical MPC tuning method is proposed for a single-input single-output (SISO) FOPDT model without active constraints. An analytical MPC tuning method for a multiple-input multiple-output (MIMO) FOPDT model is developed in Bagheri and Khakisedigh [15]. In Bagheri and Khakisedigh [16], the authors provide an MPC tuning method that is able to meet pre-described performance requirements for SISO first-order plus fractional dead time (FOPFDT) models. The decoupling condition of the MIMO FOPFDT system controlled by MPC is derived, based on which the considered multivariable MPC tuning problem is simplified as a pole placement problem Given such a simplified MPC tuning problem, an analytical tuning method is proposed to guarantee the closed-loop stability as well as the pre-specified time-domain performance for the considered system.
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