Neural-Network-Based Set-Membership Fault Estimation for 2-D Systems Under Encoding-Decoding Mechanism

In this article, the simultaneous state and fault estimation problem is investigated for a class of nonlinear 2-D shift-varying systems, where the sensors and the estimator are connected via a communication network of limited bandwidth. With the purpose of relieving the communication burden and enha...

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Vydáno v:IEEE transaction on neural networks and learning systems Ročník 34; číslo 2; s. 786 - 798
Hlavní autoři: Zhu, Kaiqun, Wang, Zidong, Chen, Yun, Wei, Guoliang
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
2-D systems
Artificial neural networks
Convexity
encoding–decoding mechanism (EDM)
Estimation
fault estimation
Neural networks
neural networks (NNs)
Optimization
Quantization (signal)
Scalars
Security
set-membership estimation (SME)
State estimation
Symmetric matrices
Task analysis
Tuning
ISSN:2162-237X, 2162-2388, 2162-2388
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Shrnutí:In this article, the simultaneous state and fault estimation problem is investigated for a class of nonlinear 2-D shift-varying systems, where the sensors and the estimator are connected via a communication network of limited bandwidth. With the purpose of relieving the communication burden and enhancing the transmission security, a new encoding-decoding mechanism is put forward so as to encode the transmitted data with a finite number of bits. The aim of the addressed problem is to develop a neural-network (NN)-based set-membership estimator for jointly estimating the system states and the faults, where the estimation errors are guaranteed to reside within an optimized ellipsoidal set. With the aid of the mathematical induction technique and certain convex optimization approaches, sufficient conditions are derived for the existence of the desired set-membership estimator, and the estimator gains and the NN tuning scalars are then presented in terms of the solutions to a set of optimization problems subject to ellipsoidal constraints. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed estimator design method.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2021.3102127