چكيده لاتين
One of the most critical issues in todayʹs world is conducting space missions with minimal cost and maximum precision. Carrying out a space mission, including the construction and launch of satellites into space, as well as their control and management, involves numerous challenges and incurs enormous costs. Therefore, any research aimed at reducing the complexity and cost of space missions is of great importance and can significantly contribute to the space industry.
In this thesis, previous research is first reviewed, and various coordinate systems and their transformations are examined. Then, the angular dynamics and kinematics of a rigid satellite are derived, and the six degrees of freedom equations for the formation flight of satellites in a leader-follower configuration are obtained. In this research, contrary to the traditional leader-follower approach, a new hypothesis is proposed in which only a limited number of follower satellites directly receive the leaderʹs information, while the remaining followers estimate the information from neighboring satellites.
Three nonlinear predictive control methods for attitude control of the satellite, based on Rodrigues, Euler, and quaternion angles, are designed. After robustifying these methods against disturbances, delays, and failures, they are simulated and evaluated. The predictive controllers are designed with the goal of controlling the attitude maneuver and turning off the reaction wheels at the end of the maneuver. In this system, the angular momentum of the wheels is considered a state variable, and the main objective is to minimize the settling time while maintaining the lowest actuator saturation time.
In this research, the combination of an extended state observer with predictive control improves the stability and accuracy of the system. Two simulation scenarios, including four followers and one leader for uncoupled equations, and one leader and one follower for coupled equations, have also been developed and simulated. Ultimately, the goal of this research is to develop an intelligent control system to optimize the control and observer coefficients using model predictive control and reinforcement learning.
Finally, the nonlinear predictive controllers are implemented on a satellite attitude control subsystem simulator. This implementation has been carried out in five different scenarios, in the presence of uncertainties and both internal and external disturbances, to evaluate the performance of the controllers and assess the stability of the system. Additionally, the selected predictive controller has been implemented both with and without the observer, and the predictive control algorithms for coupled and uncoupled consensus equations of the satellites have been simulated and validated in various scenarios.
