الفهرس 
CHAPTER 1. IntroductionOnly 14 pages are availabe for public view
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Abstract
ABSTRACT
The main objective of this thesis is to develop an intelligent system to adapt the operations of Low Earth Orbit (LEO) satellites. The received telemetry data is used to train the system to recover the satellite Attitude Determination and Control (ADCS) faults.
Classical satellite operation consist of a sequence of actions in a predefined state based on telemetry readings’ parameters; a set of pre-defined actions under certain conditions will change the state of the satellite stability. A proposed approach to this classical satellite operation planning problem is a sequence of actions that are resulted from the satellite initial state to a satellite specific state that satisfying the mission’s requirements.
The main purpose of the thesis is to send commands to the satellite to recover the satellite operation faults. To recover ADCS control faults in (LEO) satellites using Artificial Intelligent (AI), there are efficient algoritms such as fuzzy control, Support Vector Machine (SVM), Decision Tree (DT). Furthermore, using optimization algorithm like Practical Swarm Optimization (PSO) generate a high-performance control to the LEO satellites.
The thesis introduces an intelligent agent for finding solutions to classical satellite operation problems. The intelligent agent gets an accurate satellite pointing, long operation lifetime, and fast response for the satellite in-flight control. The intelligent agent technique is introduced to increase ground station autonomy and to decrease satellite recovery time based on expert personnel. This is implemented through a set of designed rules based on understanding the satellite’s different modes of telemetry readings.
The thesis presented a good demonstration of control systems that are used in (ADCS) and Electrical Power System (EPS). The ADCS has the major faults in spacecraft control, which contain the attitude control actuators such as reaction wheel and magneto-torquer for controlling the satellite orientation.
The control and power subsystems’ framework has been verified and validated using MATLAB - SIMULINK software tool. The fault injection mechanism designed to test the modeled subsystems to validate these models. The implemented faults are modeled for each system such as increase satellite torque due to over-voltage, and over current in ADCS reaction wheel actuators.
This approach is concerned with adapting the operations of (ADCS) in LEO satellites through analyzing the telemetry readings received data by mission control center, and then recover ADCS off-nominal situations.
ABSTRACT
The main objective of this thesis is to develop an intelligent system to adapt the operations of Low Earth Orbit (LEO) satellites. The received telemetry data is used to train the system to recover the satellite Attitude Determination and Control (ADCS) faults.
Classical satellite operation consist of a sequence of actions in a predefined state based on telemetry readings’ parameters; a set of pre-defined actions under certain conditions will change the state of the satellite stability. A proposed approach to this classical satellite operation planning problem is a sequence of actions that are resulted from the satellite initial state to a satellite specific state that satisfying the mission’s requirements.
The main purpose of the thesis is to send commands to the satellite to recover the satellite operation faults. To recover ADCS control faults in (LEO) satellites using Artificial Intelligent (AI), there are efficient algoritms such as fuzzy control, Support Vector Machine (SVM), Decision Tree (DT). Furthermore, using optimization algorithm like Practical Swarm Optimization (PSO) generate a high-performance control to the LEO satellites.
The thesis introduces an intelligent agent for finding solutions to classical satellite operation problems. The intelligent agent gets an accurate satellite pointing, long operation lifetime, and fast response for the satellite in-flight control. The intelligent agent technique is introduced to increase ground station autonomy and to decrease satellite recovery time based on expert personnel. This is implemented through a set of designed rules based on understanding the satellite’s different modes of telemetry readings.
The thesis presented a good demonstration of control systems that are used in (ADCS) and Electrical Power System (EPS). The ADCS has the major faults in spacecraft control, which contain the attitude control actuators such as reaction wheel and magneto-torquer for controlling the satellite orientation.
The control and power subsystems’ framework has been verified and validated using MATLAB - SIMULINK software tool. The fault injection mechanism designed to test the modeled subsystems to validate these models. The implemented faults are modeled for each system such as increase satellite torque due to over-voltage, and over current in ADCS reaction wheel actuators.
This approach is concerned with adapting the operations of (ADCS) in LEO satellites through analyzing the telemetry readings received data by mission control center, and then recover ADCS off-nominal situations.