A response surface based hierarchical approach to multidisciplinary robust optimization design

A multidisciplinary robust optimization design framework, concurrent subsystem robust design optimization, is proposed to obtain robust optimum solution in the large-scaled and coupled system. In this framework, response surfaces in the form of artificial neural networks provide information pertaining to system performance characteristics, and individual subsystems engage in performing robust optimization design in parallel while communicating with the system level. This optimization approach incorporates uncertainty analysis and generates a global robust optimum solution in an iterative fashion. Two applications are considered, and the results demonstrate that the approach yields a reasonable robust optimum solution, and it is a potential and efficient multidisciplinary robust optimization approach .     

A robust and adaptive force/position control for two cooperating robot arms under uncertainty

This paper presents a motion coordination of a two-cooperating robot arm when there are unknown system parameters and bounded input disturbances. The order of the model of the two-arm system is reduced. To control this, a force/position control scheme based on an inverse dynamics control scheme is devised. On the top of the control scheme, an adaptive control scheme to take care of parametric uncertainties, and a robust control scheme to compensate coupling forces between two arms and input disturbances are devised. The adaptive and the robust control scheme are derived based on a devised Lyapunov function. The adaptive control algorithm is practical since it does not require the feedback of the second derivative of joint angles and interacting forces. The robust control scheme guarantees that the tracking error of the leader arm and the interacting forces between two arms are confined in a certain region. Numerical examples using dual 3 degree of freedom robot arm are shown.     

A robust procedure for temperature field analysis based on order statistics

A new algorithm for locating a coolant leak through the analysis of temperature field values is presented. This algorithm is based on the measurements of air temperature at different points of the controlled area of the multiple forced circulation circuit of a nuclear power plant (NPP) and enables the determination of the dimension, location, and time of a coolant leak.     

Optimal design of a squeeze film damper using an enhanced genetic algorithm

This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.     

基于LMI优化的鲁棒控制器设计

以存在固有模型误差的单级倒立摆为被控对象,建立倒立摆的鲁棒数学模型。在不确定性因子存在的前提下,基于线性矩阵不等式方法计算得到H_∞状态反馈控制器参数K,而且给出H_∞状态反馈控制器的存在条件。通过实例仿真验证,与LQR控制相比,H_∞状态反馈控制具有更好的动态特性和抗干扰特性。     

基于磁流变减振器不确定半车悬架模型的半主动鲁棒控制研究

在分析半车悬架结构不确定性的基础上,建立了磁流变减振器半主动控制的半车模型,设计了鲁棒控制框图和鲁棒控制器.为了提高运行速度和便于工程实现,对所设计的高阶控制器进行了降阶处理,并进行了被动悬架、标准鲁棒控制半主动悬架和降阶控制器半主动悬架的频域分析.结合鲁棒控制器和半主动控制策略,在Simulink环境下构建了完成了被动悬架和降阶鲁棒控制器组成的半主动悬架时域仿真模型,对车辆在不同等级路面、不同行驶速度情况下的舒适性进行了全面的仿真研究和分析.仿真证明,所设计的鲁棒控制器和处理方法满足工程需要,相对于被动悬架车辆簧载质量垂向振动均方根值降低了14.1%以上,俯仰角架速度均方根值降低了31%以上,控制效果良好,乘坐舒适性得到提高.     

基于Kriging模型的涡轮盘优化设计方法

研究了航空发动机涡轮盘设计问题,将Kriging方法与全局约束优化算法相结合,提出了基于Kriging近似响应模型的优化求解方法,有效减少了有限元分析的次数和计算量。该优化设计方法采用正交试验设计和有限元分析方法获得涡轮盘设计空间的初始样本数据;利用已有的设计样本数据建立涡轮盘重量和应力响应近似计算的Kriging模型,在此基础上利用全局优化算法在设计空间进行设计方案优化搜索;利用有限元分析方法计算近似最优设计方案的输出响应,并以此更新已有的设计样本数据,不断提高Kriging模型的近似精度。数值计算结果表明,基于Kriging模型的涡轮盘优化设计方法不仅可以获得良好的设计结果,还能大大降低计算代价,提高设计效率。     

Robust internal model control of servo motor based on sliding mode control approach

This paper proposes a robust internal model control (IMC) based on sliding mode control (SMC) approach for high-performance motion control of a servo motor subject to uncertainties and/or disturbances. The proposed control strategy considers not only the simplicity and intuition of the IMC-based controller for a prescribed tracking performance but also the effectiveness of the SMC scheme to guarantee the robustness of the servo system. Since the performance of the IMC-based controller can be analyzed via a SMC structure, a robust control law based on the SMC technique is introduced into the IMC scheme to decrease the sensitivity to uncertainties and enhance the resistance to disturbances. Moreover, the 2-degree-of-freedom IMC integrating the robust SMC scheme is developed to further improve the control performance. The stability is analyzed based on Lyapunov theory, and the theoretical results show that a prescribed transient tracking performance and a final tracking accuracy of the servo system can be guaranteed. Comparative simulations and experiments are investigated to verify the high performance nature of the proposed control strategy.     

A new method based on LPP and NSGA-II for multiobjective robust collaborative optimization

The multiobjective robust collaborative optimization framework consists of optimization both at the system and autonomous subsystem levels. Linear physical programming is used in the system level optimization, which avoids the difficulty in choosing the multidimensional Pareto set. The non-dominated sorting genetic algorithm (NSGA-II) is used in the subsystem optimization with physical objectives. The interdisciplinary incompatibility function and physical objectives have different priority levels. At the first priority level, the best individual should be in the feasible region of the subsystem. At the second priority level, the interdisciplinary incompatibility function of the best individual should be no more than the feasibility threshold. The physical objectives are improved after the achievement of the above levels. A method for producing initial population with feasibility and diversity is proposed to improve the calculation efficiency and accuracy of the subsystem optimization at the first priority level. A method for setting dynamic feasibility threshold is proposed for the non-dominated sorting to help the physical objectives to obtain better solutions at the second priority level. Finally, the results of the speed reducer show that the presented method is efficient.     

基于参数法和贝塞尔曲线的涡轮叶片造型及其优化

为实现涡轮叶片的优化设计,采用参数造型法和贝塞尔曲线进行叶片初步造型,结合N-S方程流场模拟,并利用多目标遗传算法和序列二次算法组合优化算法,通过调节吸力面和压力面的关键控制点参数对其压力损失和转折角进行优化.结果表明该方案切实可行.     

刚架与板组合结构动力学形状优化研究

针对刚架与板组合结构动力学形状优化问题,提出一套联合运用序列二次规划 法、ＢＦＧＳ变尺度法及二次插值技术（一维搜索）,将约束优化问题转化为无约束序 列优化问题,得到了满意的结果。算例表明本文所述方法对刚架与板组合结构的有 效性,显示了算法的工程实用性,并能够推广到其它复杂结构的动力学形状优化问 题中去。     

机械产品方案优化设计系统的研究与实现

对机械产品的方案优化设计进行了研究,在此基础上用VB开发了一个方案优化设计系统,并以叉车的方案优化设计为例,阐述了系统的工作原理,并验证了系统的先进性和实用性。     

Gear hot forging process robust design based on finite element method

During the hot forging process, the shaping property and forging quality will fluctuate because of die wear, manufacturing tolerance, dimensional variation caused by temperature and the different friction conditions, etc. In order to control this variation in performance and to optimize the process parameters, a robust design method is proposed in this paper, based on the finite element method for the hot forging process. During the robust design process, the Taguchi method is the basic robust theory. The finite element analysis is incorporated in order to simulate the hot forging process. In addition, in order to calculate the objective function value, an orthogonal design method is selected to arrange experiments and collect sample points. The ANOVA method is employed to analyze the relationships of the design parameters and design objectives and to find the best parameters. Finally, a case study for the gear hot forging process is conducted. With the objective to reduce the forging force and its variation, the robust design mathematical model is established. The optimal design parameters obtained from this study indicate that the forging force has been reduced and its variation has been controlled.     

Maximizing the fundamental frequency of laminated cylindrical panels using layerwise optimization

A method of analysis is presented for determining the free vibration frequencies of cylindrically curved laminated panels under general edge conditions, and is implemented in a layerwise optimization (LO) scheme to determine the optimum fiber orientation angles for the maximum fundamental frequency. Based on the classical lamination theory applicable to thin panels, a method of Ritz is used to derive a frequency equation wherein the displacement functions are modified to accommodate arbitrary sets of edge conditions for both in-plane and out-of-plane motions. The LO approach, a recently developed scheme for laminated plates, is extended for the first time to the optimum design of curved panels. In a number of numerical examples, the accuracy of the analysis and the effectiveness of the LO approach are demonstrated.     

Fitting of robust reference surface based on least absolute deviations

Engineering surfaces comprise shape deviations namely form, waviness and roughness. For characterization of roughness, form and waviness are separated from the measured surface by establishing a reference surface that represents these deviations. This paper presents a new approach of simultaneously separating form and waviness deviations by fitting a reference surface that remains robust against the outliers such as deep grooves. A second degree polynomial and a set of sinusoidal functions are taken as basis functions to represent form and waviness respectively. A criterion of minimization of sum of absolute deviations (L₁-norm) is considered as against the commonly used least squares (L₂-norm) criterion and the reference surface obtained is found to be robust against outliers such as deep valleys in the measured surface. The superiority of the proposed fitting scheme is brought out by testing on different surfaces and comparing with the least squares method of fitting and the robust Gaussian regression filtering.     

基于熵理论的设计链优化研究

作为组织间产品设计和研发信息传递的一种特殊供应链,设计链是产品研发的发展趋势.利用信息熵理论,提出时间熵、质量熵和效用熵等概念.从优化设计链系统有序度角度,建立优化数学模型,并利用改进的蚁群算法求解.案例结果表明由实体组织构建的设计链不一定最优,以虚拟研发团队为单位,重新整合设计链中的研发活动是必要的、有效的.案例结果也证明了基于信息熵理论优化设计链的有效性.     

A normal boundary intersection approach to multiresponse robust optimization of the surface roughness in end milling process with combined arrays

Robust parameter design (RPD) has recently been applied in modern industries in a large deal of processes. This technique is occasionally employed as a multiobjective optimization approach using weighted sums as a trade-off strategy; in such cases, however, a considerable number of gaps have arisen. In this paper, the use of normal boundary intersection (NBI) method coupled with mean-squared error (MSE) functions is proposed. This approach is capable of generating equispaced Pareto frontiers for a bi-objective robust design model, independent of the relative scales of the objective functions. To verify the adequacy of this proposal, a central composite design (CCD) is developed with combined arrays for the AISI 1045 steel end milling process. In this case study, a CCD with three noise factors and four control factors are used to create the mean and variance equations for MSE of two quality characteristics. The numerical results indicate the NBI-MSE approach is capable of generating a convex and equispaced Pareto frontier to MSE functions of surface roughness, thus nullifying the drawbacks of weighted sums. Moreover, the results show that the achieved optimum lessens the sensitivity of the end milling process to the variability transmitted by the noise factors.     

鲁棒优化与多智能体协调的电梯群控调度

针对电梯群控调度过程中交通流不确定和优化求解复杂性的问题,提出一种混合鲁棒优化方法和多智能体协调的电梯群控调度方法。分析了电梯群控调度中的交通流不确定问题,建立了解决该不确定问题的电梯调度决策鲁棒优化模型。为了弥补模型求解复杂度过高的不足,进一步提出鲁棒优化和多智能体调度结合的混合调度决策方法。仿真结果表明,该方法能有效改善群控调度的性能,提高群控调度对交通模式的适应性。     

A study on the optimization method for a multi-body system using the response surface analysis

An optimization method, which minimizes the characteristic value of a system using response surface analysis, is presented. Plackett-Burman design is used as a screening method. Using the response surface analysis, second order recursive model function is estimated as an objective function. To verify the reliability of the model function, an F-test based on the analysis of variances table is used. Lastly, the sequential quadratic-programming method is used to find the value of design parameters. By applying the preceding procedure to a multi-body dynamic model, the optimization process presented in this study is verified. This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008. Sung Pil Jung received a B.S. degree in Mechanical Engineering from Ajou University in 2006. Currently he is a Ph.D candidate at Ajou University in Suwon, Korea. Mr. Jung’s research interests are in the area of multi-body & structural dynamics, optimization and computer aided engineering. Tae Won Park received a B.S. degree in Mechanical Engineering from Seoul University. He then went on to receive his M.S. and Ph.D. degrees from the University of Iowa. Dr. Park is currently a Professor at the School of Mechanical Engineering at Ajou University in Suwon, Korea.     

An optimization strategy based on a metamodel applied for the prediction of the initial blank shape in a deep drawing process

The transformation of the sheet into a product without failure and excess of material in a deep drawing operation means that the initial blanks should be correctly designed. Therefore, the initial blank design is a critical step in deep drawing design procedure. Consequently, an easy approach for engineers in predicting the initial blank shape is necessary to reduce wastage in material and to overcome the large time consumed in the classical approaches. Thus, the aim of the present investigation is to propose an automatic procedure for the quick sheet metal forming optimization. In fact, a metamodel will be build based on artificial neural networks which will be coupled then with an optimization procedure in order to predict the initial blank shape in a rectangular cup deep drawing operation. The metamodel is built from the finite element simulations using ABAQUS commercial code. This procedure allows a significant reduce of the CPU time compared to classical optimization one. The results show that the desired shape is in good agreement with the one calculated using the optimized blank shape.