Abstract
A novel event-driven model predictive control (MPC) technique is constructed for perturbed nonlinear system including both input and state constraints. The primary merit of the developed method is the event-driven input signal is constructed based on sparse control samples, and only the selected samples, rather than a continuous control signal, need to be transmitted through the network. Given such a framework, a tightened constraint is designed to satisfy the robust requirement, and an event-driven scheme is designed to lessen the computational as well as communication load of the considered MPC system. Then, theoretical requirements for guaranteeing the MPC feasibility and system convergence are figured out. Finally, proposed input signal reconstruction based MPC method is tested via simulation experiments as well as comparative study.
Highlights
Cyber-physical system (CPS) can realize the coordination of the physical and computing resources and further integrate the communication, control, computing and other functions together such that it can outperform the standard industrial system
Different from the standard time-triggered control framework, event-driven control can reduce the frequency of system control update to save computing and communication resources, and further reduce the risk of data packet loss and network delay
In order to solve the above problem, this paper proposes an input signal reconstruction approach to constructed an improved event-based model predictive control (MPC), in which only a limited number of input samples need to be transmitted through network, and the required bandwidth is significantly reduced
Summary
Cyber-physical system (CPS) can realize the coordination of the physical and computing resources and further integrate the communication, control, computing and other functions together such that it can outperform the standard industrial system. The reason is that in order to save the communication bandwidth, the proposed method only send a limited number of control samples via the network and reconstruct the continuous time input signal at the system side. Given such a setting, the input signal is completely different from the original MPC, and the conditions to guarantee the theoretical properties all need to be redesigned, which is quite complicated since the external disturbances and the change of the input signal need to be handled simultaneously. The function ζ (a, b) is Lipschitz continuous in a ∈ ∈ Rn and Lζ is the associated Lipschitz constant, if ζ (a1, b) − ζ (a2, b) ≤ Lζ a1 − a2 for a1, a2 ∈
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