Finite-Time Model Predictive Control for Constrained Continuous-Time Systems

In this paper, a finite-time model predictive control (MPC) framework is proposed for continuous-time systems subject to constraints. The proposed finite-time MPC is ex-tended from the methodology for discrete-time systems, where the control horizon is set equal to the system dimension, and only terminal cost is penalized in the optimization. Zero-Order-Holder (ZOH) is applied to ensure that no ripple exists between two consecutive sampling intervals, such that finite-time tran-sient process and zero steady-state error can be guaranteed. Combined with feedback linearization, the proposed deadbeat MPC is applicable to nonlinear continuous-time systems.