免梯度混合优化算法在卫星系统顶层设计中的应用

摘要

According to the characteristics of complicated simulation computation,large scale design space and nonlinear constraints exsting in the top design of satellite systems,a derivative-free hybrid optimization algorithm is presented,which combines treed Gaussian process (TGP),generalized pattern search (GPS) with the filter algorithm to create a new hybrid optimization algorithm.Design space is partitioned into non-overlapping sub-regions by using the TGP model,and an independent stationary Gaussian process (GP) is bulit in each sub-region to substitute for the practical model.The new "promising" points are generated utilizing the TGP,which are the combination of model-predicted values and predict errors.Then,these points are used to guide GPS search in the design space efficiently.The filter algorithm combining GPS is used to deal with nonlinear constraints.The proposed method is applied to the top design of multi-satellites cooperated observation.The results demonstrate that the hybrid algorithm has a good global search ability,which can not only increase the chance of obtaining an optimal solution but also cut down the cost of function evaluations.%针对卫星系统顶层设计中广泛存在仿真耗时、设计空间大以及非线性约束的特点,提出了免梯度混合优化算法.混合算法结合树状高斯过程(treed Gaussian process,TGP)模型、广义模式搜索和过滤法的优点,通过TGP模型将设计空间划分为互不相交的子空间,在各个子空间构建独立的高斯模型代替实际模型,并根据模型预测值和预测误差生成迭代点,进而指导模式搜索进行寻优,同时结合过滤法处理非线性约束.卫星系统中多星协同观测优化设计表明,该方法能够以较少的迭代次数获得满意解,具有很好的全局搜索特性.