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Degradation reliability analysis incorporating two-phase or even multi-phase features has become a research focus in recent years. Motivated by the fact that a practical multi-phase degradation procedure may probably involve both linear phases and nonlinear phases, a multi-phase degradation model is constructed that can consider the phase-varying nonlinear property. The unit-to-unit variability is incorporated. Meanwhile, the reliability function based on the first passage time (FPT) conception is derived, where the solution for the two-phase situation is first obtained, and the one for the multi-phase circumstance is constructed via a reclusive scheme. To verify the reasonability of the proposed reliability function, a simulation study has been complemented. Then two real applications are given to demonstrate the validity and the effectiveness of the proposed method.

Aiming at the sensor subsystem of spacecraft attitude control system equipped with gyroscopes, earth sensors and sun sensors, the observer-based fault detection and fault location problems are studied to ensure the decoupling of fault diagnosis results with actuator faults. The kinematics equation of spacecraft attitude control system and the measurement model of various sensors are given. Then the sensor subsystem is regarded as a virtual system with gyroscope outputs as input and earth sensor outputs and sun sensor outputs as outputs. On this basis, observers with different functions are designed according to different axes of spacecraft attitude control system, and the diagnostic logic is proposed correspondingly. Finally, the effectiveness of the algorithm is verified by the simulation of the satellite attitude control system.

In this paper, we focus our study on analysis of fault diagnosis performance for satellite attitude control systems subject to $l_{2}$ -norm-bounded process disturbances and measurement noises, which concerns with fault detectability and fault isolability. For an observer-based fault detection (FD), a major concern is to answer if the choice of a threshold satisfies an acceptable trade-off between fault detection rate (FDR) and false alarm rate (FAR). The smaller a threshold is, the better is the FDR, but the poorer is the FAR. In addition to this, knowledge of fault isolability is useful for answering how difficult it is to isolate a fault from another one. The main contributions of this paper are the probabilistic performance evaluation of the FD system in the context of FAR and a contribution analysis-based method of fault isolation. First, an extended $H_{i}/H_{\infty }$ optimization-based FD scheme is applied to the satellite attitude control systems and a recursive algorithm is presented to the implementation of online FD. Second, regarding the uncertain statistical characteristics of the unknown inputs, randomized algorithms are developed to verify the achievable FAR for a prescribed given threshold. Especially, without knowing the $l_{2}$ -norm boundedness of the unknown inputs, a probabilistic estimation of worst case threshold is also obtained to guarantee an acceptable level of FAR. Third, a contribution analysis-based method of fault isolation is proposed for satellite attitude control systems. Finally, the effectiveness of the proposed algorithms is verified through a satellite attitude control system.

This paper deals with the problem of fault estimation for satellite attitude control system with typical component configuration. In order to understand sensor and actuator faults propagation in the attitude control system, we have built the overall system model firstly, which includes the attitude dynamics model, sensor measurement model, attitude determination model, controller model and the moment distribution model. The faults are then considered as unknown inputs and are estimated using a classical proportional-integral observer, more over constant or time-varying fault can be estimated. The proposed observer is derived as a solution of off-line Linear Matrix Inequality (LMI) conditions. Additionally, simulation results are presented to illustrate the efficiency of the proposed method.

This paper focuses on actuator placement joint with a state feedback controller, to minimize the H ∞ norm of the closed-loop system. The actuator placement is even subject to a class of nonlinear constraints. This actuator selection problem is first formulated to be a non-convex optimization problem. Then to overcome these non-convex constraints, several procedures are provided to convert the problem into a sequential convex optimization problem, and correspondingly an optimization algorithm is given. Thruster location selection of an earth-pointing satellite is illustrated to verify the effectiveness of the proposed algorithm.

This paper investigates the actuator placement of uncertain linear systems. The designed actuator locations are subject to a class of nonlinear equality constraints, and a dynamic output feedback controller should also be derived based on measured outputs. To minimize \(H\infty \) norm of the closed-loop systems, the actuator placement problem is formulated as an uncertain non-convex optimization problem. A series of transformations are developed to convert this problem into a deterministic successive convex problem. Correspondingly, an optimization algorithm is derived based on prediction-correction procedure.

Driven by the satellite's features such as closed-loop, limited storage space and computing capacity constraint, a fault detection scheme based on the coprime factorization and Youla parameterization is proposed for the on-orbit satellite attitude control system. Based on the SISO dynamic of the satellite in pitch direction and the MIMO one in roll/yaw direction, the residuals equal to y(k)–y(k) is generated by a simple computation using the plant input and control error signals without running the state observer in parallel, therefore the computing expense is reduced to a certain extent, and the related theorems are provided synchronously. Simulation results are presented to show the performance of the proposed fault detection algorithm.

The fault diagnosability analysis for a given model, before developing a diagnosis algorithm, can be used to answer questions like “can the faultfibe detected by observed states?” and “can it separate faultfifrom faultfjby observed states?” If not, we should redesign the sensor placement. This paper deals with the problem of the evaluation of detectability and separability for the diagnosability analysis of affine nonlinear system. First, we used differential geometry theory to analyze the nonlinear system and proposed new detectability criterion and separability criterion. Second, the related matrix between the faults and outputs of the system and the fault separable matrix are designed for quantitative fault diagnosability calculation and fault separability calculation, respectively. Finally, we illustrate our approach to exemplify how to analyze diagnosability by a certain nonlinear system example, and the experiment results indicate the effectiveness of the fault evaluation methods.

Vibration of Large flexible appendage seriously reduces the stability and accuracy of satellite attitude control, which can be solved by adjusting controller via on-orbit system identification method. This paper focuses on large flexible close mode satellite antenna, and Observer/Kalman filter identification (OKID) method is put into practice to solve the problem of system identification. Mode parameters and displacement responses under impulse and white noise excitations are extracted by finite element method (FEM), and then the concept of singular entropy is introduced to reduce observation noise and determine system order. Markov parameters are computed from displacement response and mode order, which is adopted in minimal realization of state space based on eigensystem realization algorithm (ERA). Comparing with the results of FEM in numerical simulation, OKID method is much more accurate and efficient for large flexible close mode satellite antenna on-orbit system identification.

Gyroscope plays an important role in navigational systems and its drift has a direct influence on the precision. However, the gyroscope random drift series in practice are not traditional stationary time series for their time-varying means and variances, and large error cannot be avoided by traditional processing method. It is found that the statistical property of most gyroscope random drift series can meet the requirements defined by correlation coefficient stationary series. The analysis method of gyroscope drift series based on correlation coefficient stationary series model is established in this paper. The correlation coefficient stationarity testing method for gyroscope random drift series is discussed firstly. And then the modeling method process is presented. The proposed modeling procedure can efficiently improve the compensating accuracy of gyroscope random drift, because the presented method satisfactorily explains the nonstationary behavior of the gyroscope random drift series commonly existing in practice.