- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | WANG Tao, TAN Ji, LIU Dong, YANG Yejiang. Modeling of State-Dependent Switching System Based on Data-Driven[J]. Journal of Southwest Jiaotong University, 2024, 59(3): 493-500. doi: 10.3969/j.issn.0258-2724.20210579
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A switched system is a class of complex systems that integrate a series of continuous or discrete subsystems and switching mechanisms. State-dependent switching systems have not been studied in depth due to complexity. Therefore, the modeling of state-dependent switching systems is explored through the input-output trajectories of the systems. The data mining technique is used to find useful information between data and establish a more specific and explicit representation between inputs and outputs. On this basis, a framework is proposed to segment the data according to the switching time of the identified trajectory, build the subsystem model by neural network to fit its switching rules, deeply mine the information of the state-dependent switching system, and obtain the information between the subsystems and subsystems in the switching system. The experimental results show that compared with the modeling of traditional mechanism, the proposed data-driven method reduces the modeling complexity by 17.3%.
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