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Article summary:

1. Cyber-physical systems (CPS) are vulnerable to malicious network attacks, such as FDI attack, DoS attack, and replay attack.

2. Several studies have been conducted for FDI attacks in terms of modelling and design, detection and identification, and defence.

3. Model predictive control (MPC) is an advanced control strategy that has been applied to CPS, with event-triggered MPC (ETMPC) and self-triggered MPC (STMPC) being two strategies used to reduce communication and computational resources.

Article analysis:

The article provides a comprehensive overview of the research on resilient predictive control strategies of cyber–physical systems against FDI attacks. The article is well written and provides a clear explanation of the different types of network attacks against CPS, as well as the various research directions related to FDI attacks. The article also explains the differences between ETMPC and STMPC in detail.

However, there are some potential biases in the article that should be noted. For example, the article does not provide any counterarguments or explore alternative solutions for defending against FDI attacks other than resilient control strategies. Additionally, there is no discussion about possible risks associated with using these strategies or how they could be mitigated. Furthermore, while the article mentions several real cases involving cyber security problems involving FDI attacks, it does not provide any evidence to support its claims or discuss any potential implications of these cases on future research in this area.

In conclusion, while this article provides a comprehensive overview of resilient predictive control strategies for defending against FDI attacks in cyber–physical systems, it does not explore alternative solutions or discuss potential risks associated with using these strategies. Additionally, there is no evidence provided to support its claims or discussion about implications from real cases mentioned in the article.