This paper is concerned with periodic event-triggering laws in robust model predictive control (MPC) for continuous-time constrained nonlinear systems. The online optimal control problem solved at triggering times is introduced. A periodic static event-triggering condition, in which a fixed sampling time interval plays an important role in avoiding Zeno behavior, is presented to alleviate continuous checking of event detections. Then a periodic dynamic event-triggering condition is investigated to further enlarge the minimal inter-execution time. Single-mode MPC with a prediction horizon larger than the control one is considered. Sufficient conditions of recursive feasibility for the online optimal control problem are derived. In order to relax the sufficient condition of stability, Ultimately Boundedness properties are utilized in stability analysis. Finally, numerical simulation is provided to demonstrate the effectiveness of the proposed methods.

With the development of the Industrial Internet of Things (IIoT) technology, edge computing is a promising area to release the sensing and computing burdens from the overloaded center. However, in edge network scenarios, we cannot trust every node’s output since some nodes can behave maliciously by making use of the properties, such as multiple identities, heterogeneous capabilities, and mobility. In that case, trust management is widely used to solve the problem of network trustworthiness. In this article, we propose a trust evaluation framework by comprehensively considering the nodes’ malicious behaviors and heterogeneous characteristics of edge networks. Under the Bayesian framework, we use the semi-ring theory to dynamically establish mobile-edge nodes’ trust models. First, we calculate the trust value for each node with a different identity (service provider or requester). Then, we propose a security-regarded task allocation mechanism to improve the reliability of selected trusted nodes according to the matched relationship between the service requesters’ expected capability and the providers’ actual capability. Further, we conduct extensive analysis and simulations to evaluate the proposed methods in typical IIoT scenarios. The results show that the proposed method has better immunity to abnormal behaviors, including the noncooperation, malicious feedback, on–off attacks, Sybil attacks, whitewashing attack, malicious access, etc., and has higher scheduling accuracy and controllable time complexity compared to existing methods.

Proprietary (or semi-proprietary) protocols are widely adopted in industrial control systems (ICSs). Inferring protocol format by reverse engineering is im

Trusted computing is a typical active defense technology. Trust management is a core support technology of trusted computing. However, when trust management is applied in the industrial control systems, how to identify malicious behavior effectively, model trust relationships, and make a decision based on behavior trustworthiness, meanwhile how to ensure deployed trust mechanism does not affect the control network’s availability, is a significant issue that has not been solved in the previous literature. This paper proposes a trust management method against abnormal behavior of industrial control networks under active defense architecture. Firstly, we review the difficulties of trust management when applied to industrial control networks and analyze abnormal behaviors of the control operations under unknown threats. Then we extract trust information, model the trust relationship of abnormal behaviors, and establish a trust update and decision-making mechanism under the availability constraints of industrial control networks. Furthermore, we provide a deployment method of the proposed trust management in a distributed control network. Finally, we take five typical abnormal operations on control instruction in an industrial control network as an example and perform a detailed analysis and experimental verification of the proposed method. The results prove that the proposed trust management method has good immunity to abnormal behaviors of the control flow and can be deployed in an industrial control system with availability constraints.