摘要：AbstractAlthough the air traffic demand in the world has continued to increase annually in recent years, the risk of collision between an aircraft and a UAV becomes a big problem. To solve the collision problem during landing, we proposed SMPC for collision avoidance using pre-optimized feedback gain and Mixed Integer Linear Programming (MILP). Since we separate the optimization of feedback gain for minimizing uncertainties and SMPC with MILP inspired by Pinto [2017], we show that an accurate path going through obstacles can be generated at a small prediction horizon and that the feasible solutions can be obtained easily with large disturbances and complicated environments in application to an aircraft model.
