Optimization of Multiple-Impulse, Multiple-Revolution Rendezvous Problem Using Social Cognition Optimization

An approach is proposed to solve a real-world complex multiple-impulse, multiple-revolution rendezvous problem which concerns orbital perturbations such as non-central force of the earth, the attracting forces of the sun and the moon, atmospheric drag and solar radiation pressure. A generalized multiple-revolution Lambert algorithm combined with a feasible iteration rendezvous approach is developed to transform the engineering rendezvous problem to a nonlinear programming problem. A reasonable approximation method is developed to greatly simplify the computation of the earth orbit perturbations which can save much time in the resulting optimization. A two-step method, which first uses a J2J3J4 analytical orbit model and then uses a Bulirsh-Stoer integration method to integrate simplified orbital model, with a high efficient social cognition optimization (SCO) algorithm are used to solve such problem. A two-day rendezvous problem is solved to demonstrate the efficiency and effectiveness of the developed approach. The method shows that SCO algorithm which is inspired by human cognitive ability can be successfully used to optimize real-word engineering problem.