# Fault Diagnosis and Prognosis of Satellites and Unmanned Aerial Vehicles: A Review
## 3 Review Methodology
Therefore, detailed information about the measurements that are used for monitoring is not substantial and not provided in Table 7. Table 8 presents the secondary criteria that are useful for identifying the contributions of the studied works in multiagent fault diagnosis. These criteria include their architecture, communication topology and types, agent dynamic modeling, and control approaches. The architecture plays a crucial role in reducing computational complexity and system burden, as explained in Figure 5 and Section 2. In a centralized architecture, a single master observer receives information from all agents to diagnose and estimate agents' faults. While this approach involves high computational complexity, it is highly accurate. In contrast, the decentralized architecture reduces computational complexity by allowing each agent to run its own observer. However, since there is no exchange of relative information between agents, this architecture sacrifices some precision. Finally, the distributed architecture offers a trade-off between computational complexity and accuracy by assigning observers to groups of neighboring agents. Regarding communication, agents can transmit information either unidirectionally (directed) or bidirectionally (undirected). In practice, the communication within a graph can be a combination of both. Additionally, communication can either be continuous over time or event-based, where information is transmitted only when necessary. This event-based approach helps reduce the overall communication load. Moving on, we have the homogeneous and heterogeneous agent dynamic modeling and control logic criteria. The agent dynamics focus on whether the agents in the system have identical (homogeneous) or different (heterogeneous) dynamic behaviors. The control approaches in multiagent systems are divided into four main categories: consensus, formation, coverage, and flocking, depending on the mission goals. Literature shows that formation and consensus are more commonly used than other methods. It is also important to consider that, in real-world applications, the dynamics of agents in multiagent systems may vary due to operational conditions or environmental factors. This variability should be considered when working on control strategies and fault diagnosis in multiagent systems to ensure a more realistic and robust approach. An overview of all of the descriptive tables is provided in Table 1. These tables serve to guide the reader to know the defining features of the studies included in this review. For example, suppose the reader refers to this review to find a prospective methodology to compare their own with. In that case, these criteria are crucial in determining which methodologies are eligible for comparison. Or if the reader aims to find the gaps within the applications and strategies employed in the said studies, the tables serve to highlight the works that are promising in that regard. Finally, classification and organization of the utilized methodologies and studies in the literature were achieved through the content analysis, and the results are provided in Section 6.1. The identified gaps and shortcomings of the existing works are also compiled in Section 6.2 for readers' consideration. For the works in which the final quantitative results are explicitly provided, they are included in this review as well. In some works, detailed context is needed to understand the quantitative results. For these works, the final quantitative results are not included in this review to minimize the risk of misconstruing the results by the reader and inflating the text; however, their main takeaways are provided in Sections 4 and 5. Some works proposed solutions to solving persisting issues in the field and quantitative results do not highlight their contributions. Even so, among the works that do have explicit and easily understandable final quantitative results, direct comparison of these results might prove erroneous.