摘要
针对传统模糊制导律的模糊设计随意性,提出采用粒子群优化算法对模糊导引律的参数优化的方法.利用粒子群优化方法调整模糊变量隶属度,比例因子等参数,并通过反复优化使模糊推理规则接近于最优.该方法克服了模糊逻辑设计中的随意性,提高了模糊制导律的精度和鲁棒性.仿真结果表明了这种优化方法得到的模糊比例导引律明显优于传统比例导引律.
Against design randomness of traditional fuzzy guidance law, this paper suggested PSO algorithm fuzzy guidance law on the parameter optimization method. Using particle swarm optimization adjust fuzzy variables membership, parameters such as scale factor, and through repeated optimization fuzzy inference rules so close to optimal. The method overcome arbitrariness of fuzzy logic design, fuzzy guidance law increased the accuracy and robustness. Simulation results show that fuzzy proportional guidance law by such an optimization method is superior to the traditional proportional guidance law.
出处
《哈尔滨商业大学学报（自然科学版）》
CAS
2008年第1期56-59,共4页
Journal of Harbin University of Commerce：Natural Sciences Edition
基金
国家自然科学基金资助课题(50138010)
关键词
模糊导引律
粒子群算法
比例导引律
鲁棒性
fuzzy logic guidance law
particle swarm optimization algorithm
proportional navigation guidance
