# Fault Diagnosis and Prognosis of Satellites and Unmanned Aerial Vehicles: A Review
## 2 Preliminaries and Definitions  
Faults are an inevitable part of dynamic systems and must be accounted for and dealt with, particularly for applications where reliability is paramount. Faults are defined as unpredicted alterations of the system behavior occurring naturally or intentionally, prohibiting the system's subcomponents from continuing nominal operation. These faults could leave a detrimental effect on the whole system and take some time to cause failure, or in some cases, they could cause instantaneous system failures. Consequently, searching for means of diagnosing and prognosing faults is warranted to deal with faults with lasting effects as part of a health monitoring strategy. General satellite, spacecraft, and UAV fault types could be broken down into four categories: abrupt, transient, intermittent, and incipient. Abrupt malfunctions are classified as spontaneously caused by hardware failure and will not be alleviated until fully repaired. In other words, they are characterized by system changes that are faster than the system's nominal dynamics. Transient malfunctions comprise deviations from the nominal operating conditions that may disappear without external intervention. Recurring transient faults are called intermittent faults. The likelihood of intermittent faults occurring is proportional to the system complexity [9]. Finally, incipient faults are defined as malfunctions caused by the deterioration of a system over time [10]. These four fault types are illustrated in Figure 1. Faults could also be modeled as additive and multiplicative faults depending on their effects on a system's dynamics. Multiplicative faults affect a system's inputs and outputs in a multiplicative way and stem from systematic parameter variations [11]. Figure 1: Behavior of different fault types over time. The fault diagnosis process in nonlinear systems, including satellites and UAVs, involves multiple layers. The common classification used to delineate these stages of fault diagnosis includes detection, isolation, identification, estimation, and reconstruction. The term \"malfunction detection\" or \"fault detection\" refers to the capability of an analytically redundant methodology to recognize the presence of a fault. We have achieved the detection stage once our diagnostic schemes accurately identify when a fault originated. Isolation, conversely, involves determining the fault's location within the system. Therefore, a system's detection and isolation processes have temporal and spatial aspects, respectively. Detection always precedes or co-occurs with isolation but never follows it. Fault identification, estimation, and reconstruction are often used interchangeably to convey a similar concept. This stage of diagnosis aims to determine the characteristics of the malfunction. A malfunction's characteristics could include its severity, shape, depth, etc. Two main approaches for performing fault identification on a system are qualitative and quantitative. The two methods are subsets of identification techniques; however, their implementations tend to be vastly different and depend on the application. For instance, qualitative techniques necessitate a predefined set of malfunction types for classifying future occurrences as one of them or, conversely, for clustering them based on emerging malfunction types. In contrast, quantitative techniques rely on quantifying system performance degradation to achieve identification. The next step towards health monitoring is to predict the future course of faults and their effect on the RUL of a system. Prognosis becomes especially beneficial when a system is dealing with incipient faults, as its RUL could be evaluated using prognostics and lengthened by operators by taking appropriate remedying measures accordingly [12]. The results of the FDP schemes are then incorporated into fault-tolerance and recovery strategies to compensate for the malfunctions of single and multiagent systems.