A Review of Research on Diagnosability of Control Systems Based on Structural Analysis
Renjith V Ravi
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe paper presents a comprehensive overview of the research on diagnosability of control systems based on structural analysis. The focus on structural analysis as a model-based fault diagnostic approach is a notable strength of this work.
One of the strengths of the paper is its emphasis on the importance of diagnosability design, ensuring that the control system not only provides adequate fault information but also achieves fault diagnosis with efficiency and cost-effectiveness.
The development of a diagnosability index system based on structural analysis, considering structural detectability and structural isolation, is a valuable contribution to the field.
It's appreciated that the paper discusses both quantitative and qualitative aspects of diagnosability evaluation and design. This provides a well-rounded perspective on the topic.
The flow chart of diagnosability design for control systems based on structural analysis adds practical value to the paper, aiding researchers and practitioners in implementing these concepts.
The paper touches upon the current challenges and future directions in diagnosability research based on structural analysis, which is crucial for guiding further research efforts in this area.
One suggestion for improvement would be to provide more specific examples or case studies illustrating the application of structural analysis in diagnosability design. This could help readers better understand the practical implications of the concepts discussed.
Additionally, the paper could benefit from a section that discusses potential limitations or drawbacks of the structural analysis approach in diagnosability design. This would provide a more balanced view of the topic.
Questions for the Author:
Can you elaborate on any specific real-world applications where the structural analysis approach has been successfully used for diagnosability design in control systems?
In the section discussing problems and future development directions, could you provide more details on the specific challenges that researchers might encounter when applying structural analysis to diagnosability in complex control systems?
How do you see the role of advanced technologies like machine learning and artificial intelligence in enhancing the diagnosability of control systems based on structural analysis? Are there any ongoing research efforts in this direction?
Could you provide insights into the practical considerations and trade-offs involved in designing a control system with both high diagnosability and cost-efficiency, as mentioned in your paper?
Have you encountered any specific cases where the proposed diagnosability index system based on structural analysis has led to significant improvements in fault diagnosis or fault-tolerant control in control systems?
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThere are some misuses of punctuation and typing errors in the abstract. Please pay more attention to improving the writing quality.
The type of this paper is a review paper, but it does not make sense why the authors still propose a new structural model of the control system’s diagnosability. This work could be a research paper instead of a review paper.
The research of some other industry backgrounds in electrical [1], railway [2], and building [3] engineering could be cited in the introduction to expand the use of the diagnosability principle.
[1] Shu, Cheng, et al. "Fault diagnosis and fault-tolerant control scheme for open-circuit faults in three-stepped bridge converters." IEEE Transactions on Power Electronics 32.3 (2016): 2203-2214.
[2] Song, Yang, et al. "Contact wire irregularity stochastics and effect on high-speed railway pantograph–catenary interactions." IEEE Transactions on Instrumentation and Measurement 69.10 (2020): 8196-8206.
[3] Wang, Shengwei, and Youming Chen. "Fault-tolerant control for outdoor ventilation air flow rate in buildings based on neural network." Building and Environment 37.7 (2002): 691-704.
The front of the texts in Figure 3 is too small to read. Please improve the presentation quality.
Figure 4 is not well explained with sufficient details. It is a bit ambiguous to see the illustration.
Is there any demonstration to illustrate the performance of the state-of-the-art methods instead of the description of the theorem?
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe work is a review of the current state of knowledge related to diagnosability of control systems based on structural analysis. For this reason, each item of literature referenced in the text should be carefully discussed. Group references should be replaced with individual ones (e.g. [1, 2] in line 25, [3-5] in line 32 and many others). Please discuss each item of literature individually. It does not have to be extensive, but it should take into account the individual characteristics of cited work.
On the other hand, a very valuable element of this work is the tabular summary of "Methods for quantifying diagnosticability and characterization" and "Current status of research on fault diagnosis strategies based on structural analysis" with detailed references to the particular works.
Editing and language notes:
- drawings are difficult to read (too much small text, text collisions with frames),
- in many places, the sentences are too long and their meaning is lost. I suggest using shorter sentences,
- punctuation requires careful correction (eg. dots after chapter numbering are sometimes present and sometimes not, similarly in the case of captions for tables, figures and other elements).
Comments on the Quality of English Language- in many places, the sentences are too long and their meaning is lost. I suggest using shorter sentences,
- punctuation requires careful correction (eg. dots after chapter numbering are sometimes present and sometimes not, similarly in the case of captions for tables, figures and other elements).
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsHaving meticulously reviewed the manuscript, I am pleased to report that the author has taken all of my concerns into account and has effectively addressed them.
Reviewer 2 Report
Comments and Suggestions for AuthorsAll my comments have been well addressed.
