| 引用本文: | 任佳,高晓光,张艳.移动威胁情况下的无人机路径规划[J].控制理论与应用,2010,27(5):641~647.[点击复制] |
| REN Jia,GAO Xiao-guang,ZHANG Yan.Path planning based on model predictive control algorithm under moving threat[J].Control Theory and Technology,2010,27(5):641~647.[点击复制] |
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| 移动威胁情况下的无人机路径规划 |
| Path planning based on model predictive control algorithm under moving threat |
| 摘要点击 2594 全文点击 2586 投稿时间：2008-12-01 修订日期：2009-07-04 |
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| DOI编号 10.7641/j.issn.1000-8152.2010.5.CCTA081332 |
| 2010,27(5):641-647 |
| 中文关键词 无人机 路径规划 模型预测控制 转换量测卡尔曼滤波 |
| 英文关键词 UAV path planning MPC CMKF |
| 基金项目 国家自然科学基金资助项目(60774064). |
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| 中文摘要 |
| 针对路径规划中存在快速移动威胁, 提出基于威胁状态预测的模型预测控制(MPC)算法, 进行无人机动态路径规划. 采用转换量测卡尔曼滤波算法预测移动威胁的状态, 弥补MPC算法无法有效预测快速移动威胁的不足. 根据移动威胁的预测状态, 评估无人机的威胁代价, 与路径长度等约束共同构建目标函数, 通过滚动优化目标函数, 得到一系列在线控制量, 完成路径规划. 仿真结果表明该方法可以有效躲避移动威胁, 进行实时路径规划. |
| 英文摘要 |
| Combining with the prediction of fast moving threat, the model predictive control(MPC) algorithm is adopted in the dynamic path planning for uninhabited air vehicles(UAVs). By using the converted measurement Kalman filter(CMKF) algorithm, the states of moving targets are predicted, and then the threats against UAV are evaluated, together with the length of path, to establish the cost function. The path planning is accomplished by obtaining a series of on-line control values which are figured out by minimizing the cost function in receding horizon. Finally, the application efficiency of MPC in path planning is validated by the simulation results. |
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