Fault-Tolerant Optimized Control of Switched Complex Networks via an Adaptive Dynamic Programming Approach

The paper addresses the fault-tolerant optimized control of switched complex networks with unknown state and actuator fault. A proportional-integral intermediate observer is constructed to estimate unknown elements by relaxing known boundary requirement. An optimized controller is proposed to achieve fault-tolerant synchronization via adaptive dynamic programming scheme. A critic neural network is employed to solve the value of the Hamilton–Jacobi–Bellman equation. Sufficient conditions are established to ensure the uniformly ultimately bounded synchronization performance. Finally, an example is simulated to deliver the effectiveness of the proposed approach.

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Publication Details

Journal
IEEE Transactions on Automation Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tase.2025.3582898
Citations
5
Primary Topic
Adaptive Dynamic Programming Control
Type
article
Field-Weighted Citation Impact
7.52

Funders

Controls
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article

Fault-Tolerant Optimized Control of Switched Complex Networks via an Adaptive Dynamic Programming Approach

Guangdeng Zong, Chen Wang, Mouquan Shen, Tingwen Huang et al.
5 citations
IEEE Transactions on Automation Science and Engineering
Adaptive Dynamic Programming Control
7.52
article

Fault-Tolerant Optimized Control of Switched Complex Networks via an Adaptive Dynamic Programming Approach

Guangdeng Zong, Chen Wang, Mouquan Shen, Tingwen Huang, Qing-Guo Wang
article en
5 citations

Abstract

The paper addresses the fault-tolerant optimized control of switched complex networks with unknown state and actuator fault. A proportional-integral intermediate observer is constructed to estimate unknown elements by relaxing known boundary requirement. An optimized controller is proposed to achieve fault-tolerant synchronization via adaptive dynamic programming scheme. A critic neural network is employed to solve the value of the Hamilton–Jacobi–Bellman equation. Sufficient conditions are established to ensure the uniformly ultimately bounded synchronization performance. Finally, an example is simulated to deliver the effectiveness of the proposed approach.

IEEE Transactions on Automation Science and EngineeringVol. 22
Nanjing Tech University (CN), Shenzhen University (CN), Tiangong University (CN), Beijing Normal University (CN), Shenzhen Technology University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Adaptive Dynamic Programming Control
7.52
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Fault-Tolerant Optimized Control of Switched Complex Networks via an Adaptive Dynamic Programming Approach — Guangdeng Zong, Chen Wang, et al. · IEEE Transactions on Automation Science and Engineering (2025) | TGRS Research Map | TGRS