Title: Dual control algorithms for fault diagnosis of stochastic systems with unknown parameters

Authors: Sun Jinkun; Yang Kang

Addresses: School of Electronic Information Engineering, Xi'an Technological University, Xi'an, 710021, China ' School of Electronic Information Engineering, Xi'an Technological University, Xi'an, 710021, China

Abstract: This paper researches the problem of fault diagnosis for stochastic system characterised by slowly changing, unknown parameters. This paper puts forward a conception of logic parameter decay rate based on the threshold, and has designed a rolling control algorithm learning control law based on Kalman filtering theory and LQG control law, while this algorithm can estimate the parameters, on the side of the parameter learning, the system has good fault tolerance ability, thus more accurate fault detection and isolation. The simulation results verify the effectiveness of the proposed method.

Keywords: fault diagnosis; parameter decay rate; Kalman filter; LQG control; rolling control algorithm.

DOI: 10.1504/IJICT.2019.102476

International Journal of Information and Communication Technology, 2019 Vol.15 No.2, pp.132 - 144

Received: 25 Jan 2018
Accepted: 08 Apr 2018
Published online: 27 Sep 2019 *

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