Innovation Approach Based Sensor FDI in LEO Satellite Attitude Determination and Control System

In this study Fault Detection and Isolation (FDI) in the attitude determination and control system of Low Earth Orbit (LEO) satellite is investigated. Attitude determination system uses algebraic method. This method is based on computing any two analytical vectors in the reference frame and measuring these vectors in the body coordinate system (Barishev & Krilov, 1968; Wertz, 1988). As measuring devices, magnetometers and sun sensors are used. The satellite attitude is estimated via Extended Kalman Filter (EKF). The Kalman filter approach to attitude determination and control is quite sensitive to the any measurement malfunctions (abnormal measurements, sudden shifts in the measurement channel, and other difficulties such as decrease of instrument accuracy, an increase of background noise, etc.). If the condition of operation of the measurement system does not correspond to the models, used in the synthesis of filter, then these changes resulting from some possible failures at the measurement channels significantly decrease the effectiveness of the attitude determination and control system. It is important to achieve fault-tolerance in the design of satellite attitude determination and control systems. For this purpose it is required to perform the sensor FDI in these systems. Many fault detection methods have been developed to detect and identify faults in dynamic systems by using analytical redundancy (Zhang & Li, 1997; Rago et al., 1998; Larson et al., 2002; Lee & Lyou, 2002). In (Zhang & Li, 1997; Rago et al., 1998) the algorithms for detection and diagnosis of multiple failures in the dynamic systems are described. They are based on the Interacting Multiple-Model (IMM) estimation algorithm, which is one of the most costeffective adaptive estimation techniques for systems involving structural as well as parametric changes. The proposed algorithms provide an integrated framework for fault detection, diagnosis, and state estimation. In methods, described in these works, the faults are assumed to be known, and the Kalman filters are designed for the known types of faults. As the approach requires several parallel Kalman filters, and the faults should be known, it can be used in limited applications. In (Larson et al., 2002) an analytical redundancy-based approach for detecting and isolating sensor, actuator, and component (i.e., plant) faults in complex dynamical systems, such as aircraft and spacecraft is developed. The method is based on the use of constrained Kalman filters, which are able to detect and isolate such faults by exploiting functional relationships O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg