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Event-triggered fault detection for discrete-time LPV systems with application to a laboratory tank system
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John Wiley and Sons Ltd
, 2018 , Article)
This paper investigates a new event-triggered fault detection methodology for discrete-time dynamic systems characterized by linear parameter-varying models. An event-based linear parameter-varying observer is presented ...
Event-Triggered Fault Detection for Networked Control Systems Subject to Packet Dropout
(
Wiley-Blackwell
, 2018 , Article)
This paper investigates the problem of event-triggered fault detection for discrete-time networked systems subject to packet dropout. The main aim of the proposed approach is to efficiently use the communication network ...
Nonlinear Suboptimal Tracking Controller Design Using State-Dependent Riccati Equation Technique
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Article)
In this brief, a new technique for solving a suboptimal tracking problem for a class of nonlinear dynamical systems is presented. Toward this end, an optimal tracking problem using a discounted cost function is defined and ...
A single dynamic observer-based module for design of simultaneous fault detection, isolation and tracking control scheme
(
Taylor and Francis Ltd.
, 2018 , Article)
The problem of simultaneous fault detection, isolation and tracking (SFDIT) control design for linear systems subject to both bounded energy and bounded peak disturbances is considered in this work. A dynamic observer is ...
Event-triggered simultaneous fault detection and tracking control for multi-agent systems
(
Taylor and Francis Ltd.
, 2019 , Article)
The main aim of this study is to design distributed simultaneous fault detection and control units for multi-agent systems subject to limited communication and energy resources. For this purpose, each agent is equipped ...
Sensor fault detection and isolation of an industrial gas turbine using partial adaptive KPCA
(
Elsevier Ltd
, 2018 , Article)
In this paper, sensor fault detection and isolation of time-varying nonlinear dynamical systems is studied by utilizing an adaptive kernel principal component analysis (KPCA) solution as a useful method to overcome the ...