  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 non-separable ones is a prior request and a crucial
issue to be resolved. Aiming at the above problem, this paper presents two
dual-level model predictive control (MPC) algorithms for two-timescale
dynamical systems with unknown bounded disturbance and input constraint. 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
the high and low levels. As a key 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 non-separable 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 reported, which show the effectiveness of the proposed
algorithms.
