岩石蠕变模型的参数较多,为得到参数的全局最优解,应用微进化算法(M icroevolution A lgorithm,MA)对岩石蠕变模型非定常参数进行了反演分析。算法以实测蠕变值与理论计算值之间的最小二乘误差为优化准则函数,直接反演计算蠕变模型参数...岩石蠕变模型的参数较多,为得到参数的全局最优解,应用微进化算法(M icroevolution A lgorithm,MA)对岩石蠕变模型非定常参数进行了反演分析。算法以实测蠕变值与理论计算值之间的最小二乘误差为优化准则函数,直接反演计算蠕变模型参数。计算结果表明,微进化算法可最大限度地利用所有试验数据,避免传统优化算法初始参数选取的困难,且算法简单有效,计算精度高于混沌粒子群优化算法。该方法也可推广应用于其它蠕变模型的参数反演,具有较高的工程应用价值。展开更多
In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scena...In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scenario,on the basis of geometric relationship of each phase trajectory,the problem of trajectory planning is transformed to parameter optimizing,and then auxiliary population-based quantum differential evolution algorithm(AP-QDEA)is applied as a tool to optimize the objective function,and the design parameters of the whole homing trajectory are obtained.The proposed AP-QDEA combines the strengths of differential evolution algorithm(DEA)and quantum evolution algorithm(QEA),and the notion of auxiliary population is introduced into the proposed algorithm to improve the searching precision and speed.The simulation results show that the proposed AP-QDEA is proven its superior in both effectiveness and efficiency by solving a set of benchmark problems,and the multiphase homing scheme can fulfill the requirement of fixed-points and upwind landing in the process of homing which is simple in control and facile in practice as well.展开更多
文摘岩石蠕变模型的参数较多,为得到参数的全局最优解,应用微进化算法(M icroevolution A lgorithm,MA)对岩石蠕变模型非定常参数进行了反演分析。算法以实测蠕变值与理论计算值之间的最小二乘误差为优化准则函数,直接反演计算蠕变模型参数。计算结果表明,微进化算法可最大限度地利用所有试验数据,避免传统优化算法初始参数选取的困难,且算法简单有效,计算精度高于混沌粒子群优化算法。该方法也可推广应用于其它蠕变模型的参数反演,具有较高的工程应用价值。
基金Project(61273138) supported by the National Natural Science Foundation of ChinaProjects(KJ2016A169,KJ2015A242) supported by the University Natural Science Research Key Project of Anhui Province,ChinaProject(ZRC2014444) supported by the Talents Program of Anhui Science and Technology University,China
文摘In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scenario,on the basis of geometric relationship of each phase trajectory,the problem of trajectory planning is transformed to parameter optimizing,and then auxiliary population-based quantum differential evolution algorithm(AP-QDEA)is applied as a tool to optimize the objective function,and the design parameters of the whole homing trajectory are obtained.The proposed AP-QDEA combines the strengths of differential evolution algorithm(DEA)and quantum evolution algorithm(QEA),and the notion of auxiliary population is introduced into the proposed algorithm to improve the searching precision and speed.The simulation results show that the proposed AP-QDEA is proven its superior in both effectiveness and efficiency by solving a set of benchmark problems,and the multiphase homing scheme can fulfill the requirement of fixed-points and upwind landing in the process of homing which is simple in control and facile in practice as well.
