Characterization of all nonlinear stabilizing controllers via observer-based kernel representations

Summary The objective of this paper is to develop performance‐based fault detection (FD) and fault‐tolerant control (FTC) schemes for a class of nonlinear systems. To this end, the representation forms of nonlinear systems with faults and the controller parameterization forms are studied first with the aid of the nonlinear factorization technique. Then, based on the stable kernel representation and the stable image representation of the faulty nonlinear system, the stability performance of the closed‐loop system is addressed, respectively. The so‐called fault‐tolerant margin is defined to evaluate the system fault‐tolerant ability. On this basis, two performance‐based FD schemes are developed aiming at detecting the system performance degradation caused by system faults. Furthermore, to recover the system stability performance, two performance‐based FTC strategies are proposed based on the information provided by the FD unit. In the end, a numerical example and a case study on the three‐tank system are given to demonstrate the proposed results.

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“…Throughout this paper, only the L 2 stability is under consideration. In the following, the definitions of the SKR and SIR are introduced …”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

Han

Chen

et al. 2019

Intl J Robust & Nonlinear

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Data-driven fault detection for Lipschitz nonlinear systems: From open to closed-loop systems

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Data-driven spiking neural networks for intelligent fault detection in vehicle lithium-ion battery systems

Wu,

Tian,

Tao

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Engineering Applications of Artificial Intelligence

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Characterization of all nonlinear stabilizing controllers via observer-based kernel representations

Cited by 23 publications

References 20 publications

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

Data-driven fault detection for Lipschitz nonlinear systems: From open to closed-loop systems

Data-driven spiking neural networks for intelligent fault detection in vehicle lithium-ion battery systems

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