Reentry trajectory optimization based on improved genetic algorithm and sequential quadratic programming

An optimization method combining improved genetic algorithm with sequential quadratic programming was proposed for the design of reusable launch vehicle reentry trajectory.The advantages of being insensitive to initial values and global convergence of genetic algorithm(GA),and rapid convergence and high precision of sequential quadratic programming(SQP)were developed.The weakness including solution vibration of GA and small convergence radius,being sensitive to initial values and easy to fall into a local extremum of SQP was overcome.The improved genetic algorithm with simulated annealing penalty function was employed to globally search design space and sequential quadratic programming for local optimization,while the direct collocation method was used to discretize optimal control problem into nonlinear programming problem.A global high-precision solution can be obtained without initial guess.Results show the correctness,effectiveness,insensitive to initial values and good robustness of the algorithm.