Fault Detection and Avoidance for Spacecraft Failure using PSO Algorithm | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 9, Volume 28, ICEEM2019-Special Issue, 2019, Page 300-305 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2019.64936 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Yassin M. Yassin* 1; Wael Murtada2; Ahmed El Mahallawy3 | ||||
| 1Ground Station, Mission Control Center Flight Director National Authority for Remote Sensing and Space Science (NARSS) Cairo, Egypt | ||||
| 2On-Board Computer & Space software, PH.D National Authority for Remote Sensing and Space Science (NARSS) Cairo, Egypt | ||||
| 3department of Computer Science and Engineering, Ph.D Monoufia University Monoufia, Egypt | ||||
| Abstract | ||||
| Fault detection algorithm design of satellite inflight control is important for most remote sensing satellites. The responsibility of a satellite attitude control system always keeps the satellite in a stable mode. A satellite control mode contains standby, imaging and detumbling modes. Before we start imaging, we used to prepare an attitude control system to change satellite angles according to payload camera planning schedule to shoot a specific area of interest. After imaging is complete, the attitude control changes satellite angles back to nadir (zero tilting angels). Some control problems may cause failures which put the satellite in a detumbling mode due to accumulated torque on reaction wheel of the satellite. Artificial intelligent design algorithm of particle swarm optimization (PSO) is proposed to control the satellite in real-time mode, which decreases the angular velocity received from the satellite. This approach calculates the difference between the real-time measurement and the designed angular velocity (∆θ) within the satellite communication session time. The Matlab customization function implements PSO controller. The mathematical model of satellite attitude control system has been designed according to the satellite dynamics and kinematics laws. The approached mathematical model is implemented using Simulink Matlab tools. | ||||
| Keywords | ||||
| Fault diagnosis algorithm; particle swarm optimization (PSO); satellite control; and Euler’s moment equations | ||||
| References | ||||
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