PySCP: A Multiple-Phase Optimal Control Software Using Sequential Convex Programming

Optimal control problems are common in aerospace engineering. A Python software program called PySCP is described for solving multiple-phase optimal using sequential convex programming methods. By constructing a series of approximated second-order cone subproblems, approaches to the solution original problem an iterative way. The key components detail, including convexification, discretization, and adaptive trust region method. convexification first-order differential dynamic equation implemented successive linearization. Six discretization methods, zero-order hold, Runge-Kutta, three hp pseudospectral collocation so that different types can be tackled efficiently. Adaptive method employed, robust convergence achieved. Both free-final-time fixed-final-time solved by software. application demonstrated on with varying complexity. provides researchers useful toolkit solve wide variety programming.