摘要
提出了一种基于粒子群优化算法(PSO)的弹道辨识及仿真的技术。根据弹道质心运动方程模型,以小脑模型开关控制器神经网络(CMAC)为核心构建了辨识网络,利用PSO算法控制辨识与仿真的实现。仿真试验表明,利用PSO算法实现弹道辨识比BP算法辨识精度高,收敛性好。
In this paper, a trajectory recognition and simulation technique based on PSO (particle swarm optimizer) is proposed. According to trajectory centric motion equations, and taking CMAC neural network as its core, a trajectory recognition network is built up. The PSO algorithm controls the realization of recognition and simulation. Simulation results reveal that the proposed recognition technique based on PSO has higher precision of recognition and better convergence than those based on BP algorithm.
出处
《系统仿真学报》
CAS
CSCD
2004年第11期2517-2519,2532,共4页
Journal of System Simulation
关键词
粒子群优化
弹道辨识
小脑模型开关控制器
BP算法
PSO (particle swarm optimizer)
trajectory recognition
cerebella model articulation controller
BP algorithm
