Journal article
Co-Design of adaptive event generator and asynchronous fault detection filter for Markov jump systems via genetic algorithm
IEEE Transactions on Cybernetics, Early Access
2022
Abstract
This article investigates the co-design problem of adaptive event-triggered schemes (AETSs) and asynchronous fault detection filter (AFDF) for nonhomogeneous higher-level Markov jump systems, involving the hidden Markov model (HMM), higher-level Markov chain (MC), and conic-type nonlinearities. The transformation of the system transition probability can be reflected by the designed higher-level MC. An HMM with another conditional transition probability is applied to detect higher-level Markov processes and make the system be more practical. In order to balance the utilization of network resources and system performance, a novel AETS is proposed and used in the construction of the AFDF. By the Lyapunov theory, sufficient conditions are given to ensure the existences of the AETS and AFDF. It is not only an appropriate tradeoff between the utilization of network resources and system performance, but also reduces the conservatism. Finally, a numerical example is given to detect the faults effectively by the co-designed AFDF.
Details
- Title
- Co-Design of adaptive event generator and asynchronous fault detection filter for Markov jump systems via genetic algorithm
- Authors/Creators
- X. Zhang (Author/Creator)H. Wang (Author/Creator)J. Song (Author/Creator)S. He (Author/Creator)C. Sun (Author/Creator)
- Publication Details
- IEEE Transactions on Cybernetics, Early Access
- Publisher
- IEEE
- Identifiers
- 991005544969007891
- Copyright
- © 2022 IEEE.
- Murdoch Affiliation
- School of Engineering and Energy; Centre for Water, Energy and Waste
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.29 Automation & Control Systems
- 4.29.30 Robust Control Systems
- Web Of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics
- ESI research areas
- Computer Science