Your browser doesn't support javascript.
loading
A Distributed Fault Diagnosis and Cooperative Fault-Tolerant Control Design Framework for Distributed Interconnected Systems.
Li, Xue; Fan, Zhikang; Wang, Shengfeng; Qiu, Aibing; Mao, Jingfeng.
Afiliación
  • Li X; School of Electrical Engineering, Nantong University, Nantong 226019, China.
  • Fan Z; School of Electrical Engineering, Nantong University, Nantong 226019, China.
  • Wang S; School of Electrical Engineering, Nantong University, Nantong 226019, China.
  • Qiu A; School of Electrical Engineering, Nantong University, Nantong 226019, China.
  • Mao J; School of Electrical Engineering, Nantong University, Nantong 226019, China.
Sensors (Basel) ; 22(7)2022 Mar 23.
Article en En | MEDLINE | ID: mdl-35408095
ABSTRACT
This paper investigates a design framework for a class of distributed interconnected systems, where a fault diagnosis scheme and a cooperative fault-tolerant control scheme are included. First of all, fault detection observers are designed for the interconnected subsystems, and the detection results will be spread to all subsystems in the form of a broadcast. Then, to locate the faulty subsystem accurately, fault isolation observers are further designed for the alarming subsystems in turn with the aid of an adaptive fault estimation technique. Based on this, the fault estimation information is used to compensate for the residuals, and then isolation decision logic is conducted. Moreover, the cooperative fault-tolerant control unit, where state feedback and cooperative compensation are both utilized, is introduced to ensure the stability of the whole system. Finally, the simulation of intelligent unmanned vehicle platooning is adopted to demonstrate the applicability and effectiveness of the proposed design framework.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: China