The dynamic-Q optimization method: An alternative to Sequential Qudratic Programming

In this paper, a constrained optimization method, called the Dynamic-Q method, is presented. Simply stated, the method consists of applying an existing dynamic trajectory optimization algorithm to successive spherical quadratic approximations of the actual optimization problem. The Dynamic-Q algorithm has the advantage of having minimal storage requirements, thus making it suitable for problems with large numbers of variables. The Dynamic-Q method is tested and results obtained are compared to results for a sequential quadratic programming (SQP) method. Indications are that the new method is robust and efficient, and a particularly well suited to practical engineering optimization problems.