电光与控制, 2015, 22 (7): 43, 网络出版: 2015-08-25
量子粒子群算法在地磁匹配航迹规划中的应用
Geomagnetic Navigation Path Planning Based on Quantum Particle Swarm Optimization Algorithm
地磁匹配导航 航迹规划 量子粒子群算法 geomagnetic matching navigation path planning Quantum Particle Swarm Optimization (QPSO) algorit
摘要
针对基本粒子群算法在飞行器地磁匹配航迹规划中容易陷入局部收敛的问题,借鉴粒子群算法和量子进化算法,将量子粒子群算法应用在基于地磁匹配的航迹规划中。结合飞行器的性能约束和地磁匹配自身特点,设计了一种适用于地磁匹配航迹规划的评价函数作为适应度函数。仿真结果表明,量子粒子群算法具有较快的收敛速度且改善了最优解,验证了量子粒子群算法应用于地磁匹配航迹规划的有效可行性。
Abstract
The basic Particle Swarm Optimization (PSO) algorithm has the problem of easy to get into local optimum when used in geomagnetic navigation path planning.Based on PSO and Quantum Evolution (QE) algorithm,the Quantum Particle Swarm Optimization (QPSO) algorithm was applied to solve the problem.Combined with constraints of aircrafts and characteristics of geomagnetic matching navigation,an adaptive evaluation function was designed as fitness function.The simulation results show that QPSO has faster convergence speed and can avoid falling into local optimum effectively,which prove the availability and feasibility of QPSO for applying to path planning based on geomagnetic matching navigation.
李婷, 张金生, 王仕成, 吕志峰, 卢兆兴. 量子粒子群算法在地磁匹配航迹规划中的应用[J]. 电光与控制, 2015, 22(7): 43. LI Ting, ZHANG Jin-sheng, WANG Shi-cheng, LYU Zhi-feng, LU Zhao-xing. Geomagnetic Navigation Path Planning Based on Quantum Particle Swarm Optimization Algorithm[J]. Electronics Optics & Control, 2015, 22(7): 43.