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一种用于低空飞行的在线航迹重规划方法
引用本文:唐强,张新国,刘锡成. 一种用于低空飞行的在线航迹重规划方法[J]. 西北工业大学学报, 2005, 23(2): 271-275
作者姓名:唐强  张新国  刘锡成
作者单位:1. 西北工业大学,自动化学院,陕西,西安,710072
2. 西北工业大学,自动化学院,陕西,西安,710072;飞行自动控制研究所,陕西,西安,710065
3. 飞行自动控制研究所,陕西,西安,710065
摘    要:研究了飞行器在低空飞行时的在线航迹重规划问题,并提出了一种新方法。通过引入最小威胁曲面的概念生成三维航迹搜索空间,利用一个有限项的多项式函数来逼近最小威胁曲面中的三维航迹在二维水平面内的投影,将航迹规划问题转为在一个一元函数多项式系数空间中的搜索寻优。利用粒子群优化算法完成优化,并借鉴预测控制中滚动时域优化的思想,以在线滚动进行优化的方式完成航迹的在线重规划。实验表明该方法能够规划出合理的航迹并满足实时性要求。

关 键 词:航迹规划 在线重规划 最小威胁曲面 航迹投影 滚动优化 粒子群优化
文章编号:1000-2758(2005)02-0271-05
修稿时间:2004-03-02

Exploring an Online Method of Vehicle Route Re-Planning for Low Altitude Flight
Tang Qiang,Zhang Xinguo,LIU Xicheng. Exploring an Online Method of Vehicle Route Re-Planning for Low Altitude Flight[J]. Journal of Northwestern Polytechnical University, 2005, 23(2): 271-275
Authors:Tang Qiang  Zhang Xinguo  LIU Xicheng
Affiliation:Tang Qiang~
Abstract:Up to now, to our best knowledge, papers in the open literature have not yet succeeded in solving the very difficult problem of real-time 3-D vehicle route re-planning to take into account the many uncertainties that actually occur during flight. In this paper, we aim to explore solving this very difficult problem. First of all, the concept of SOMR (Surface of Minimum Risk) is presented to form the search space of 3-D route. Then a polynomial function with finite terms is used to approach the horizontal projection of the 3-D route in the SOMR. So the original planning problem is simplified into that of searching the best series of values in the coefficient space of the polynomial function. This optimization problem is solved with PSO (particle swarm optimization). To realize online re-planning, the idea of receding horizon optimization is introduced to re-plan the route in a way of rolling optimization. This idea and PSO combine to complete the whole planning process. Via the method mentioned above, the generated routes can be re-planned in real-time as new information becomes available, and it has the abilities of terrain following, terrain avoidance and threat avoidance. While no general conclusion can be drawn for the real-time capability of our method, we performed simulations with Matlab 5.3 for a specific flight mission. Simulation results show that: (1) for three conditions, each step of re-planning is estimated to be completed on an average within 2.94 s, 3.31 s and 1.64 s respectively; (2) for re-planning of each step, the allowable time as assumed by us is 10 s.
Keywords:real-time 3-D vehicle route re-planning  surface of minimum risk (SOMR)  route horizontal projection  rolling optimization  particle swarm optimization (PSO)
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