Mixed fault diagnosis scheme for satellite formation

Abstract

Purpose The purpose of this paper is to present a solution for the uncertain fault with the propulsion subsystem of satellite formation, using the Lur’e differential inclusion linear state observers (DILSOs) and fuzzy wavelet neural network (FWNN) to perform fault detection and diagnosis. Design/methodology/approach The uncertain fault system cannot be described based on the accurate differential equations. The set-value mapping is introduced into the state equations to solve the problem of uncertainty, but it will cause output uncertainty. The problem can be solved by linearization of Lur’e differential inclusion state observers. The Lur’e DILSOs can be used to detect uncertain fault. The fault isolation and estimation can be performed using the FWNN. Findings The mixed approach from fault detection and diagnosis has featured fast and correct to found the uncertain fault. The simulation results to indicate that the methods of design are not only effective but also have the advantages of good approximation effect, fast detection speed, relatively simple structure and prior knowledge and realization of adaptive learning. Research limitations/implications The hybrid algorithm can be extensively applied to engineering practice and find uncertain faults of the propulsion subsystem of satellite formation promptly. Originality/value This paper provides a fast, effective and simple mixed fault detection and diagnosis scheme for satellite formation.

Reconfigurable Fault-Tolerant Control for Spacecraft Formation Flying Based on Iterative Learning Algorithms

“…In this frame, the x, y, and z components are referred to as radial direction, tangential direction, and normal direction, respectively. Considering space perturbation, the linear C-W equation [9,26] describes the relative dynamic motion between the deputy spacecraft and the chief spacecraft and is as follows: We define system state as ( ) [ , , , , , ] T t x y z x y z = q , and the relative motion equation in (1) can be written into the following state-space model.…”

“…where () t F represents control force results from thruster faults and the fault distribution matrix H = B . Considering space perturbation, the linear C-W equation [9,26] describes the relative dynamic motion between the deputy spacecraft and the chief spacecraft and is as follows:…”

“…Corollary 1. Suppose that Q 1 = I 3 , if there exist a positive definite symmetric matrices P ∈ R 6×6 , a positive scalar γ, and matrices L 2 ∈ R 3×6 , Y ∈ R 6×6 such that (8), (9), and (11) hold, then the ILO (5) can reconstruct constant thruster bias faults asymptotically, and the observer gain matrix L 1 can be obtained by L 1 = P −1 Y.…”

“…To guarantee the high control performance, reliability, and safety of spacecraft formation flying systems, fault diagnosis and fault-tolerant control (FTC) are challenging problems that need to be handled urgently for spacecraft formation flying systems in practice. In view of these, fault diagnosis and FTC for spacecraft formation control systems have attracted considerable 2 of 18 attention in both research and practical applications during the past decade, and great progress has been achieved in recently published work in the literature [8][9][10][11][12][13][14][15][16].…”

“…In [8], fuzzy rule-based fault diagnosis approaches were proposed for the leaderfollower spacecraft formation architecture. In [9], a fault detection and diagnosis approach, based on the Lur'e differential inclusion theory and fuzzy wavelet neural network, was proposed for the propulsion subsystem of spacecraft formation. In [10], based on the linear parameter varying technique, nonlinear observers were respectively explored to detect, isolate, and estimate actuator faults in a multi-satellite formation system, and less conservative linear matrix inequality (LMI) conditions were provided for observer design.…”