文章基本信息

标题：Stochastic Optimal Control for Collision Avoidance and Landing
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作者：Yuji Shimizu ; Takeshi Tsuchiya
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：12
页码：37-42
DOI：10.1016/j.ifacol.2019.11.066
语种：English
出版社：Elsevier
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.
关键词：KeywordsAircraft controlControl algorithms implementationStochasticMPCCollision avoidance