A Metamodeling Method Based on Support Vector Regression for Robust Optimization

Metamodeling techniques have been used in robust optimization to reduce the high computational cost of the uncertainty analysis and improve the performance of robust optimization problems with computationaUy expensive simulation models.Existing metamodels main focus on polynomial regression(PR),neural networks(NN)and Kriging models,these metamodeis are not well suited for large-scale robust optimization problems with small size training sets and high nonlinearity.To address the problem,a reduced approximation model technique based on support vector regression(SVR)is introduced in order to improve the accuracy of metamodels.A robust optimization method based on SVR is presented for problems that involve high dimension and nonlinear.First appropriate design parameter samples are selected by experimental design theories,then the response samples are obtained from the simulations such as finite element analysis,the SVR metamodel is constructed and treated as the mean and the variance of the objective performance functions.Combining other constraints,the robust optimization model is formed which can be solved by genetic algorithm(GA).The applicability of the method developed is demonstrated using a case of two-bar structure system study.The performances of SVR were compared with those of PR,Kriging and back-propagation neural networks(BPNN),the comparison results show that the prediction accuracy of the SVR metamodel was higher than those of other metamodels under uncertainty.The robust optimization solutions are near to the real result,and the proposed method is found to be accurate and efficient for robust optimization.This reaserch provides an efficient method for robust optimization problems with complex structure.     

Robust state estimation based on sliding mode observer for aeroelastic system

This paper concerns the application and demonstration of sliding mode observer for aeroelastic system, which is robust to model uncertainty including mass and stiffness of the system and various disturbances The performance of a sliding mode observer is compared with that of a conventional Kalman filter to demonstrate robustness and disturbance decoupling characteristics. Aeroelastic instability may occur when an elastic structure is moving even in subcritical flow speed region Simulation results using sliding mode observer are presented to control aeroelastic response of flapped wing system due to various external excitations as well as model uncertainty and sinusoidal disturbances in subcritical incompressible flow     

MULTIDISCIPLINARY ROBUST OPTIMIZATION DESIGN

Because uncertainty factors inevitably exist under multidisciplinary design environment, a hierarchical multidisciplinary robust optimization design based on response surface is proposed. The method constructs optimization model of subsystem level and system level to coordinate the coupling among subsystems, and also the response surface based on the artificial neural network is introduced to provide information for system level optimization tool to maintain the independence of subsystems, i.e. to realize multidisciplinary parallel design. The application case of electrical packaging demonstrates that reasonable robust optimum solution can be yielded and it is a potential and efficient multi-disciplinary robust optimization approach.     

Robust Collaborative Optimization Method Based on Dual-response Surface

A novel method for robust collaborative design of complex products based on dual-response surface (DRS-RCO) is proposed to solve multidisciplinary design optimization (MDO) problems under uncertainty. Collaborative optimization (CO) which decomposes the whole system into a double-level nonlinear optimization problem is widely Accepted as an efficient method to solve MDO problems. In order to improve the quality of complex product in design process, robust collaborative optimization (RCO) is developed to solve those problems under uncertain conditions. RCO does opfmiTation on the linear sum of mean and standard deviation of objective function and gets an optimal solution with high robustnmess. Response surfaces method is an important way to do approximation in robust design. DRS-RCO is an improved RCO method in which dual-response surface replaces system uncertainty analysis module of CO. The dual-response surface is the approximate model of mean and standard deviation of objective function respectively. In DRS-RCO, All the information of subsystems is included in dual-response surfaces. As an additional item, the standard deviation of objective function is added to the subsystem optimization. This item guarantee both the mean and standard deviation of this subsystem is reaching the minima at the same time. Finally, a test problem with two coupled subsystems is conducted to verify the feasibility and effectiveness of DRS-RCO.     

基于拓扑优化的加工中心十字滑台结构设计

基于零件结构静态和动态性能及轻量化的总体设计目标,利用结构拓扑优化方法完成了立式加工中心十字滑台的结构设计,解决了零件结构静、动刚度不足问题及质量过重导致的机床加速性能不良等问题。首先,详细分析了十字滑台的工况。其次,针对同时满足十字滑台具有良好的静动态性能并减轻其质量的设计需求,采用结构的柔度最小和基频最大为目标函数以及体积比为约束的多目标、多工况的结构拓扑优化方法,进行了十字滑台的结构拓扑优化设计,获得了其结构构型。最后,分析并对比了十字滑台新结构和原有结构的刚度、固有频率、质量及机床加速性能,验证了新结构具有良好的性能。     

Vehicle lateral stability management using gain-scheduled robust control

This paper deals with the design of a yaw rate controller based on gain-scheduled H_∞ optimal control, which is intended to maintain the lateral stability of a vehicle. Uncertain factors such as vehicle mass and cornering stiffness in the vehicle yaw rate dynamics naturally call for the robustness of the feedback controller and thus H_∞, optimization technique is applied to synthesize a controller with guaranteed robust stability and performance against the model uncertainty. In the implementation stage, the feed-forward yaw moment by driver’s steer input is estimated by the disturbance observer in order to determine the accurate compensatory moment. Finally, HILS results indicate that the proposed yaw rate controller can satisfactorily improve the lateral stability of an automobile.     

稳健优化的表述、不确定分析与求解策略

首先通过对优化问题的表述,说明稳健优化与传统确定性优化的区别。稳健优化需进行不确定性分析,为此对目标的均值和方差同时进行优化。然后分析和比较了蒙特卡罗法、基于敏感度法、解析法、基于代理模型法等不确定性分析方法的特点,其中着重介绍了基于代理模型的不确定性分析方法。最后讨论了2类求解稳健优化问题的策略：加权法和多目标遗传算法。     

基于环境健壮性的班组武器动力学优化

采用健壮性设计理论及优化设计策略,建立了基于环境健壮性的优化设计数学模型,针对在环境温度及洁净度因素干扰下班组武器动力学性能的健壮性进行了优化设计,分析了主要运动件质量及复进簧刚度对于班组武器运动特性的影响,依据SN比确定了最佳健壮性设计方案及设计因数最佳水平。方差分析结果表明,枪机总质量是最显著影响因数,通过合理调配可使武器的动力特性达到最稳定,研究所获结论为该武器样机的研制提供了重要理论指导。     

基于桨叶模态修型的直升机减振优化

基于Hamilton原理推导了模态修型减振优化的有限元动力学模型,通过修改桨叶的剖面刚度和线密度来改变结构的动力学模态。以最小振动载荷为目标函数,以桨叶剖面刚度及质量为设计变量,以桨叶的频率、自转惯量、质量及模态修型参数等为约束条件,进行了减振优化。算例表明:在约束条件都满足的情况下,优化后,3/转的桨根剪力减小了55.4%,4/转的桨根剪力减小了66.5%,5/转的桨根剪力减小了53.4%,优化效果明显。     

自动扶梯桁架结构的有限元轻量化分析

针对自动扶梯式电梯在安全性能和轻量化设计上的矛盾,首先,运用有限元方法计算了原设计中自动扶梯的结构强度和刚度性能,分析了原设计中存在的不足;然后,结合结构参数对性能影响的灵敏度分析,提出了结构改进设计的主要对象;最后,在改善结构强度和刚度性能的基础上,应用优化设计技术对电梯桁架结构的板材厚度进行了优化分析.研究结果表明,重新设计后的电梯桁架结构的强度提高了21.1％,刚度提高了24.6％,极大地改善了结构性能;同时,结构质量减轻了7.2％,取得了轻量化的效果.     

A robust optimization using the statistics based on kriging metamodel

Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.     

基于双向渐进结构优化法的柔性机构设计

基于双向渐进结构优化法提出一种面向柔性机构的拓扑优化设计策略。由于采用0/1离散拓扑设计变量和启发式变量更新机制,双向渐进结构优化法一般适用于结构刚度相关的凸优化设计问题。柔性机构以最大化驱动端的位移为设计目标,属于典型的非凸优化问题,难以直接应用该方法开展相应的设计。针对于此,通过定义一种由驱动位移和刚度特性（柔顺度）加权平均的优化目标函数,实现基于双向渐进结构优化法的柔性机构设计。该优化目标函数具有双重功效：（1）通过逐步（设计迭代步）衰减刚度特性的贡献,实现优化问题由刚度设计向驱动设计的动态演化,可应用双向渐进结构优化法开展机构的拓扑构型设计;（2）通过调节加权系数,实现对设计机构的驱动性能和刚度特性的灵活匹配调控,可有效抑制铰链的形成、防止应力集中引起的失效。典型算例的设计结果显示,提出的发展的演化式设计策略可实现稳健且高效的柔性机构设计。     

Robust force control of a hybrid actuator using quantitative feedback theory

The use of hydraulic systems in industrial applications has become widespread due to their advantages in efficiency. In recent years, hybrid actuation systems, which combine electric and hydraulic technology into a compact unit, have been adapted to a wide variety of force, speed and torque requirements. A hybrid actuation system resolves energy consumption and noise problems characteristic of conventional hydraulic systems. A new, low-cost hybrid actuator using a DC motor is considered to be a novel linear actuator with various applications such as robotics, automation, plastic injection-molding, and metal forming technology. However, this efficiency gain is often accompanied by a degradation of system stability and control problems. In this paper, to satisfy robust performance requirements, tracking performance specifications, and disturbance attenuation requirements, the design of a robust force controller for a new hybrid actuator using Quantitative Feedback Theory (QFT) is presented. A family of plant models is obtained from measuring frequency responses of the system in the presence of significant uncertainty. Experimental results show that the hybrid actuator can achieve highly robust force tracking even when environmental stiffness set-point force varies. In addition, it is understood that the new system reduces energy use, even though its response is similar to that of a valve-controlled system.     

基于稳健优化的真空断路器弹簧操动机构分闸弹簧设计

将稳健设计思想和优化设计思想相结合,将加工误差等因素引起的影响考虑在设计变量的容差之中,寻求弹簧刚度系数误差最小化,且以弹簧结构参数在其容差内变化时弹簧刚度系数的最大波动量的最小化为优化目标,建立了具有多目标、两级优化的分闸弹簧稳健优化设计数学模型。提出了系列求解该数学模型的优化策略。将稳健优化设计数学模型应用于10kV、12．5kA真空断路器弹簧操动机构中的分闸弹簧的设计,有效改善了分闸弹簧的力特性及真空断路器的分合闸速度特性。     

基于Pro/E和ADAMS的高压断路器机构仿真分析

针对高压开关操动机构的动力学问题,通过Pro/E建立仿真模型,以Parasolid格式导入ADAMS/View,利用多体动力学仿真分析软件ADAMS,对断路器机构系统进行动态仿真建模与分析,为断路器设计和优化提供了良好的平台。分析结果表明,该高压断路器结构响应能满足设计要求,增大合闸弹簧刚度和超程弹簧刚度可以降低合闸时间和动触头弹跳量。     

Robust control using recursive design method for flexible joint robot manipulators

A flexible joint robot manipulator can be regarded as a cascade of two subsystems: link dynamics and the motor dynamics. Using this structural characteristic, we propose a robust nonlinear recursive control method for flexible manipulators. The recursive design is done in two steps. First, a fictitious robust control for the link dynamics is designed as if it has a direct control input. As the fictitious control, a nonlinear H _∞-control using energy dissipation is designed in the sense of L ₂-gain attenuation from the disturbance caused by uncertainties to performance. In the process, Hamilton-Jacobi (HJ) inequality is solved by a more tractable nonlinear matrix inequality (NLMI) method. In the second step, the other fictitious and the actual robust control are designed recursively by using the Lyapunov’s second method. The proposed robust control is applied to a two-link robot manipulator with flexible joints in computer simulations. The simulation results show that the proposed robust control has robustness to the model uncertainty caused by changes in the link inertia and the joint stiffness.     

基于有限元法的结构优化与灵敏度分析

探讨了用有限元法进行结构优化与灵敏度分析的一般思路 ;介绍了优化与灵敏度分析的基本理论及利用 I-DEAS软件进行优化的过程。以某轻型客车的车架为例 ,选弯曲刚度、扭转刚度和一阶扭转频率为性能约束 ,根据灵敏度分析结果 ,按高刚度、轻质量的要求 ,选择出有效的设计变量进行了重量最轻或性能最优的结构优化 ,并得出相应的结论。     

长缝光谱仪主结构的稳健优化设计

为了减轻长缝光谱仪（LSS）主结构的重量,保持结构响应高稳定性,对LSS主结构进行稳健优化设计。分析结构尺寸加工公差和材料参数波动等不确定性因素对LSS主结构稳健性的影响。调整结构尺寸加工公差,建立以结构质量为目标、以结构频率为约束的LSS主结构稳健优化模型。应用蒙特卡罗模拟方法和蚁群优化算法对稳健优化模型进行优化求解。稳健优化后的结构质量为33Kg,比初始质量减少17.5%;频率为77 Hz。稳健优化最优结构质量较确定性优化略高,但结构响应更为稳定,具备抵抗尺寸波动和材料参数波动的能力。满足设计要求。采用的设计方法对类似结构的稳健优化设计有参考意义。     

基于双响应面模型的碰撞安全性稳健性优化设计

建立稳健的车体耐撞结构是提高汽车碰撞安全性的有效途径.传统的耐撞性优化设计,由于忽视制造工艺、材料特性和边界条件中存在的不确定因素,导致汽车碰撞安全性能不够稳健.近年来,稳健性设计得到广泛的关注,并在汽车工业中得到应用.将稳健性设计方法应用到汽车碰撞安全性设计中,以某轿车的前纵梁为研究对象,运用双响应面方法对其进行稳健性优化设计.采用拉丁超立方抽样(Latin hypercube sampling,LHS)方法和最小二乘方法创建碰撞响应的二阶多项式双响应面模型,将材料特性作为不确定性因素.稳健性优化后,对前纵梁碰撞性能的稳健性与优化前进行对比分析.分析结果表明,该稳健性设计方法精度较高;经稳健性优化后,前纵梁碰撞性能的稳健性获得了显著提高,且质量减少了3.32％.     

基于运动学、刚度和动力学性能的并联机构有序递进三级优化设计及其应用

提出一种基于运动学、刚度和动力学性能的并联机构有序递进三级优化策略,即分别应用遗传算法（GA）、粒子群算法（PSO）、差分进化算法（DE）三种智能算法,以工作空间性能和运动/力传递性能为目标的尺度参数优化方法,又在优化尺度参数基础上,以机构承载刚度和整体刚度为目标进行构件截面参数优化,再在优化尺度参数和截面参数基础上,以动力学灵巧度和能量传递效率为目标进行构件质量参数优化,从而使得机构的尺度、截面及质量参数达到最优。以一种零耦合度三平移一转动（SCARA）并联操作手为例,运用矢量法建立了并联操作手的运动学模型,通过工作空间性能和运动/力传递性能两个运动学指标,优化其尺度参数;运用虚拟弹簧法得到该并联操作手的刚度模型,通过对三维模型的参数识别得到其柔度矩阵,并分析了承载刚度、整体刚度两个刚度性能指标,优化了构件的截面参数;利用动力学普遍方程导出了该并联操作手的动力学模型,通过动力学灵巧度和能量传递效率两个动力学性能指标,优化了构件的质量参数。最终,该并联操作手的运动学、刚度和动力学综合性能达到最优,也得到了一些尺度、截面及质量参数的设计准则。