# A Review of Research on Diagnosability of Control Systems Based on Structural Analysis
## 6 Research Outlook  
The diagnosability design based on structural analysis mainly suffers from the following shortcomings. Firstly, the computational cost of the MSO algorithm is significant, and the computational efficiency is low. Secondly, the influence of system noise interference and other uncertainties on the residuals generated based on the MSO set is not comprehensively considered. Furthermore, the design of the diagnosability in the underdetermined part has not been taken into account. Lastly, the theory of reconfigurability in the analysis stage and the design of the system's reconfigurability to ensure the system's fault tolerance are not addressed. Therefore, the future research focuses are as follows:  
(1) Comprehensive diagnostic architecture design  
The basic idea of comprehensive diagnostic optimization design is to satisfy the diagnosability and reconfigurability needs as the basis. Comprehensive diagnostic design finds the optimal set of diagnostic resources in the system resource space. It aims to reduce the diagnostic time and diagnostic cost. The allocation of diagnostic test resources is the key to measuring the level of diagnosability, which is related to the overall fault diagnosis performance. It occupies an essential position in the design of diagnosability. (2) Research on structural characterization based on structural underdetermination system  
With the existing fault diagnosis methods based on structural analysis, most of the objects studied are overdetermined or just-determined systems. When the system under study is overdetermined, a large amount of the existing literature provides a variety of fault detection or fault isolation methods to analyze and study. It guides us in selecting the residuals, in generating them to detect faults, etc. When the system under study is just-determined, the methods for adding sensors to make it an overdetermined system that satisfies the fault isolation requirements are given. Subsequently, the existing methods for overdetermined systems are utilized to study it. However, for underdetermined systems, there is less literature related to them that is based on structural analysis. As industrial systems become increasingly large and complex, different devices of the same design may also be distributed in other areas, leading to a localized system becoming an underdetermined system. Therefore, it is necessary to conduct an in-depth study of the structural characteristics of underdetermined systems. (3) Optimized configuration of sensors for underdetermined systems  
In the existing structural analysis method, most of the research objects related to the optimal configuration of sensors are for overdetermined or just-determined systems. In contrast, the research on the optimal configuration of sensors for the underdetermined system is less. Typically, the sensor configuration problem involves understanding how to add sensors to increase the system's redundancy, how to identify which variables can be measured by additional sensors, how to use fewer sensors, how to optimize the placement of sensors for better diagnostic results, and so on. Most of the existing research on these issues is on overdetermined or just-determined systems. For the sensor configuration of underdetermined systems, it is also necessary to consider the effect of adding sensors on the correlation (dependency) between the system's internal components; this is worthy of in-depth exploration. (4) Multi-fault detection and isolation  
With the existing structural analysis methods, faults are usually set as single faults, i.e., only one fault occurs at a specific moment when the system fails. In the existing literature,there are more studies on fault diagnosis methods with single-fault assumptions, and the theories are more mature. However, there are fewer studies on multi-fault systems. In dynamical systems, the multi-fault problem is a bit more complicated.