A Dual-Level Model Predictive Control Scheme for Multitimescale Dynamical Systems

Xinglong Zhang

doi:10.1109/TSMC.2022.3207315

A Dual-Level Model Predictive Control Scheme for Multitimescale Dynamical Systems

2023-03-01

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DOI：10.1109/TSMC.2022.3207315

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So far, many control algorithms have been developed for singularly perturbed systems. However, in many industrial processes, enforcing closed-loop fast-slow dynamics for peculiarly nonseparable ones is a prior request and a crucial issue to be resolved. Aiming at the above problem, this article presents two dual-level model predictive control (MPC) algorithms for multitimescale dynamical systems with unknown bounded disturbances and input constraints. The proposed algorithms, each one composed of two regulators working in slow and fast time scales, are designed to generate closed-loop separable dynamics at high and low levels. As a prominent feature, the proposed algorithms are not only suitable for singularly perturbed systems but also capable of imposing separable closed-loop performance for dynamics that are nonseparable and strongly coupled. The recursive feasibility and convergence properties are proven under suitable assumptions. The simulation results on controlling a boiler turbine (BT) system, including the comparisons with other classic controllers, are demonstrated, which show the effectiveness of the proposed algorithms.

Keywords:

Heuristic algorithms

Couplings

Control systems

Stability criteria

Predictive control

Prediction algorithms

Dynamical systems

Boiler turbine (BT) control

dual-level

linear systems

model predictive control (MPC)

separable dynamics

A Dual-Level Model Predictive Control Scheme for Multitimescale Dynamical Systems

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