Aperiodic Robust Model Predictive Control for Constrained Continuous-Time Nonlinear Systems: An Event-Triggered Approach

Abstract

The event-triggered control is a promising solution to cyber-physical systems, such as networked control systems, multiagent systems, and large-scale intelligent systems. In this paper, we propose an event-triggered model predictive control (MPC) scheme for constrained continuous-time nonlinear systems with bounded disturbances. First, a time-varying tightened state constraint is computed to achieve robust constraint satisfaction, and an event-triggered scheduling strategy is designed in the framework of dual-mode MPC. Second, the sufficient conditions for ensuring feasibility and closed-loop robust stability are developed, respectively. We show that robust stability can be ensured and communication load can be reduced with the proposed MPC algorithm. Finally, numerical simulations and comparison studies are performed to verify the theoretical results.

Event‐triggered model predictive control for disturbed linear systems under two‐channel transmissions

“…For the case of single sample, the data packet in Figure 1 only contains the information and t k . The actual control is rather than in References 10 and 17 for s ∈ [ t k , t k + 1 ). As shown in Figure 2, the function of the fusion unit under single sample is the same as the zero‐order‐hold manner.…”

“…In Reference 15, two event‐triggering conditions, whose selection depends on whether the actual states enter into the terminal region of the dual‐mode MPC strategy 16 or not, were designed to reduce the transmission rates further. Meanwhile, many results of the ETMPC scheme have also been proposed for the continuous systems in which the system performance and constraints can be satisfied all the time instead of only at the discrete instants for discrete systems 17 . A robustness constraint approach was proposed for constrained continuous nonlinear systems in Reference 18 and extended to event‐triggered robust MPC in References 10,19.…”

“…A robustness constraint approach was proposed for constrained continuous nonlinear systems in Reference 18 and extended to event‐triggered robust MPC in References 10,19. Reference 17 took advantage of the tightened state constraint 20 and removed the requirement of the prediction horizon for guaranteeing the feasibility in Reference 10. Besides, a time‐constrained scheme 21 was designed by evaluating the time when the optimal state trajectory enters a local set.…”

Event-Triggered ${H}_{\infty}$ Control for Uncertain Markov Jump Systems With Nonlinear Input

“…In [10], [11], event-based control problems have been solved for switched linear system by asynchronous control approach, such that leads to an major improvement in event-triggered control theory. By combining event-driven scheme, model predictive control strategy can achieve a satisfactory performance and reduce the computation load, such as in [12], [13]. Recently, adaptive event-triggered controller is designed for uncertain nonlinear systems [14].…”

Double-layered nonlinear model predictive control based on Hammerstein–Wiener model with disturbance rejection

“…Model predictive control (MPC) is the most popular advanced control method in industrial control technology and academics, which can effectively overcome the disturbance and uncertainty and easily handle the constrain of controlled variables and manipulated variables. [1][2][3][4][5] It is a kind of model-based closed-loop optimization control strategy. The principle of the method is to predict the dynamic behavior of the system and to proceed rolling optimization and to achieve feedback correction of model error.…”