An Evolutionary Framework for Multi-Objective Trajectory Design and Robust Model Predictive Control in Long-Range Rendezvous Missions

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Samsam, Sanaz




This thesis presents an optimization architecture for on-orbit servicing mission design in the long-range rendezvous phase. We develop a methodology to generate Pareto Optimal trajectories for long-range rendezvous of a servicing satellite with a moving target. The methodology employs a multi-impulse shape-based trajectory planning algorithm for in-plane orbit transfer, based on the two-body problem. The Pareto Optimal trajectories from this set are then obtained using a constrained multi-objective optimization algorithm developed based on the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). To robustly follow the generated reference trajectories in a J2-perturbed orbital environment, we propose a Nonlinear Model Predictive Control (NMPC) scheme. The control signals are velocity increments at the time of applying each impulse, and the variable horizon is considered to be the time difference between every two impulses in the reference trajectory. To solve the optimization problem that is defined in the controller, the genetic algorithm is implemented.


Engineering - Aerospace
Applied Mechanics




Carleton University

Thesis Degree Name: 

Master of Applied Science: 

Thesis Degree Level: 


Thesis Degree Discipline: 

Engineering, Aerospace

Parent Collection: 

Theses and Dissertations

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