面向机器人优化设计的GA-非均匀Kriging-梯度投影混合全局优化算法  

Hybrid Global Optimization Method Based on Dynamic Kriging Metamodel and Gradient Projection Method for Optimal Design of Robot

作　　者：杨志军[1,2] 陈超然[2,3] 黄观新 YANG Zhijun;CHEN Chaoran;HUANG Guanxin(State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment,Guangdong University of Technology,Guangzhou 510006;Guangdong Provincial Key Laboratory of Micro-Nano manufacturing Technology and Equipment,Guangdong University of Technology,Guangzhou 510006;Department of Electromechanical Engineering,Shantou Polytechnic,Shantou 515078)

机构地区：[1]广东工业大学省部共建精密电子制造技术与装备国家重点实验室,广州510006 [2]广东工业大学广东省微纳加工技术与装备重点实验室,广州510006 [3]汕头职业技术学院机电工程系,汕头515078

出　　处：《机械工程学报》2019年第11期61-68,共8页Journal of Mechanical Engineering

基　　金：国家自然科学基金(91648108,11702065,51875108);广东省自然科学基金(2015A030312008);中国博士后科学基金(2017M622623)资助项目

摘　　要：针对机器人优化设计等工程应用中普遍存在的黑箱问题,提出了一种高效、稳定的遗传算法-非均匀Kriging-梯度投影混合全局优化(Hybrid global optimization,HGO)算法。该方法使用非均匀Kriging模型对目标函数进行评估,能够在不苛求近似模型全局精度的情况下保证优化过程的精度,并节省大量计算时间。使用梯度投影法对遗传算法种群进行变异,可以在提升优化收敛效率的同时确保优化约束条件,从而可以避免使用并不严格的罚函数法处理约束函数。为验证算法的有效性和优越性,将本算法应用于两个数学测试算例和一个模块化机械臂截面优化实例中,并与其他优化算法比较。结果表明,本算法能够兼顾结果精度、优化效率和算法稳定性,发挥更好的综合性能,从而实现对工程问题的全局优化设计。In order to solve the black-box problem which is commonly existed in engineering applications such as robots,an efficient and stable hybrid global optimization(HGO)algorithm based on genetic algorithm,non-uniform Kriging metamodel and gradient projection method is proposed.In the proposed algorithm,non-uniform Kriging metamodel is used to evaluate the objective function,which can ensure the accuracy of the optimization process without demanding the global accuracy of the approximate model and save a lot of computation.Moreover,gradient projection method is used to mutate the population of genetic algorithm,which can improve the convergence efficiency of optimization and ensure the optimization constraints to avoid using the non-strict penalty function method to deal with constraints.To validate its effectiveness and superiority,the proposed algorithm is applied to two mathematical test examples and a modular manipulator optimization example,then compared with other optimization algorithms.The results show that the proposed algorithm can balance the accuracy of the results,the optimization efficiency and the stability of the algorithm to achieve a better comprehensive performance,so as to achieve a global optimization design for engineering problems.

关 键 词：遗传算法 KRIGING模型 梯度投影法 全局优化 黑箱问题 

分 类 号：TG156[金属学及工艺—热处理]