Secure Change Control for Supply Chain Systems via Dynamic Event Triggered Using Reinforcement Learning under DoS Attacks

Author:

Fan Lingling1ORCID,Zhang Bolin1,Xiong Shuangshuang1,Li Qingkui1

Affiliation:

1. Department of Control Engineering, School of Automation, Beijing Information Science & Technology University, Beijing 100192, China

Abstract

In this paper, a distributed secure change control scheme for supply chain systems is presented under denial-of-service (DoS) attacks. To eliminate the effect of DoS attacks on supply chain systems, a secure change compensation is designed. A distributed policy iteration method is established to approximate the coupled Hamilton–Jacobi–Isaacs (HJI) equations. Based on the established reinforce–critic–actor (RCA) structure using reinforcement learning (RL), the reinforced signals, performance indicators, and disturbance input are proposed to update the traditional time-triggered mechanism, and the control input is proposed to update the dynamic event-triggered mechanism (DETM). Stability is guaranteed based on the Lyapunov method under secure change control. The simulation results for supply chain systems show the effectiveness of the secure change control scheme and verify the results.

Funder

National Key Research and Development Program of China

Project of Cultivation for Young Topnotch Talents of Beijing Municipal Institutions

R&D Program of Beijing Municipal Education Commission

National Natural Science Foundation (NNSF) of China

Publisher

MDPI AG

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