基于改进蝠鲼觅食算法的汽车前桥轻量化优化

汽车前桥结构是汽车的核心部件之一，在汽车设计中具有举足轻重的地位。为提高汽车前桥轻量化优化的收敛速度和精度，提出一种基于蝠鲼自身防卫策略改进的蝠鲼算法。采用六个经典的测试函数对改进蝠鲼算法进行性能测试验证，结果表明改进的蝠鲼算法具有良好的收敛速度和收敛精度。在此基础上，运用改进的蝠鲼算法对汽车前桥进行轻量化优化设计，优化结果表明经过94次迭代之后可以获得最优解，汽车前桥优化后的总质量从51.95 kg降低为43.24 kg,降低了16.75%。通过分析经典测试函数和汽车前桥案例的结果可知，改进的蝠鲼算法是一种高效的优化算法，对以后的工程优化问题和算法改进具有参考意义。     

可变形机翼结构设计与实验分析

利用平面多闭环连杆机构,提出一种可变形机翼结构,并对该结构进行数学建模,利用结构数学模型,在Matlab中进行了机构的运动轨迹仿真分析。为了验证机构曲率调节能力及气动特性,建立了机构的三维模型,进行了运动学仿真及空气动力学仿真分析。为了获得更好的气动特性,基于传统人工鱼群优化算法,提出一种改进的人工鱼群优化算法,利用经典优化算法测试函数测试了该算法的性能。采用该优化算法对可变形机翼进行结构优化。在理论研究的基础上,加工了实验样机,并进行了相关实验测试。     

一种基于小生境的混合遗传退火算法

分析遗传算法和模拟退火算法混合优化策略的构造出发点 ,融合小生境技术的思想 ,提出一种以遗传算法和模拟退火算法为子算法的基于小生境技术的混合遗传退火算法———NGSA算法 ,并对该算法的特点和优化性能作了定性分析。结合典型多峰值测试函数———Shubert函数的求解实验 ,说明NGSA算法具有较强的全局和局部搜索能力 ,能够高效地寻找到多个全局极值 ,且参数选择不必过分严格 ,是一种优化能力、效率和可靠性较高的多峰值优化方法。最后 ,讨论了该算法在机械学科的广泛应用背景。     

粒子群优化算法中惯性权重的研究

惯性权重是粒子群优化算法中的关键参数,文章对惯性参数进行了系统的研究,在此基础上,分析了固定权重,典型的线性递减惯性权重,步长较小的线性递减惯性权重时收敛性能的影响.通过对4个测试函数的仿真实验,验证了它们各自的全局收敛性和收敛速度,说明了惯性权重在粒子群优化算法中有很大的自由度.     

粒子群优化算法及其在结构优化设计中的应用

介绍了粒子群优化算法的原理和实现方法,分析了该算法的主要参数对搜索方向的影响。将粒子群优化算 法与遗传算法在优化过程和搜索技术方面进行了对比。利用粒子群优化算法与遗传算法分别对测试函数和桁架结 构优化设计问题进行求解,将两种算法的计算结果进行了对比。计算结果表明在满足相同的计算精度的前提下,粒 子群优化算法的效率更高,利用粒子群优化算法可求解机翼结构优化设计问题,因此,粒子群算法是一种有效的优 化方法,适用于大型复杂结构优化设计。     

基于多目标连续蚁群算法的热精轧过程负荷分配策略研究

本文通过对蚁群算法的进一步研究,提出了多目标连续蚁群算法（MOCACO）。算法中,蚂蚁能够在连续空间内爬行,蚂蚁分泌的信息素只留存于当前位置并且通过蚂蚁移动前后的Pareto支配关系对信息素进行更新,每次优化计算后可得到一组非支配最优解。在此基础上,提出了基于MOCACO算法的热精轧负荷分配优化策略,并通过仿真实验证明了MOCACO算法在解决热精轧负荷分配问题上的有效性与优越性。     

协同进化MDO算法在鱼雷总体设计中的应用

现有基于梯度的多学科设计优化算法难于处理具有离散和整数设计变量、设计空间非凸或不连通的多学科设计优化问题,并且倾向于收敛到接近初始点的局部最优点.针对以上问题,分别采用合作协同进化算法和分布式协同进化算法进行鱼雷总体设计研究,并对2种模型进行了对比分析.     

基于改进型粒子群优化算法的双辊薄带振动铸轧压下控制系统优化

振动铸轧辊的周期性振动是诱发Kiss点波动的主要因素,亦可导致轧制力波动,最终造成铸轧薄带纵向厚度不均,为此,对粒子群优化算法进行改进,提出了在粒子群收缩因子算法基础上添加扰动因子的优化算法,并依托四种不同类型的测试函数对该算法进行了仿真分析。结合AMESim、MATLAB联合仿真平台进行仿真验证,并将该算法应用于双辊薄带振动铸轧机液压压下控制系统上进行实验验证,结果表明,在粒子群收缩因子算法基础上添加扰动因子的优化算法在收敛速度及求解精度上明显优于基本粒子群优化算法、粒子群收缩因子算法、带极值扰动的粒子群优化算法,使得实际辊缝宽度误差降低至0.1mm。该算法适用于双辊薄带振动铸轧的中试生产,增强了振动铸轧工艺的稳定性。     

光纤光栅曲线重建算法中的曲率连续化研究

在医疗内窥镜形状检测方面,传感器的定位精度对病灶的诊断和手术方案的制定起到了关键性的作用。本文在基于利用大长度的光纤光栅曲率传感器进行形状重建的方法上,对抛物、正弦和反正切形式下的理论曲线和实际曲线弧段中的曲率连续化方法进行了优化性研究,提出了三次样条曲率连续化方法。经过实验数据分析得出在算法优化后,对接近光纤光栅弯曲极限的实际曲线弧段中,X、Y方向上使用三次样条曲率连续化法后的坐标点平均拟合精度能够相对提升4.8%和2.2%,成功对二维曲线重建进行了精度改进。同时,曲线的重建响应时间为19 ms,能够满足实时性要求。     

一种用于多目标约束优化的改进进化算法

当前求解多目标优化的进化算法主要考虑如何处理相互冲突的多个目标间的优化,很少考虑对约束条件处理的问题.对此,给出了一种基于双群体搜索机制的改进差分进化算法,以求解多目标约束优化问题.采用两个不同种群,分别保存可行个体与不可行个体的双群体约束处理策略,利用基于Pareto的分类排序多目标优化技术,完成对进化个体解的评价.并通过群体混沌初始化、自适应交叉和变异操作来提高基本差分进化算法的性能.对三个经典测试函数的仿真结果表明,文中算法在均匀性、逼近性及收敛速度三方面均优于非支配排序遗传算法,而收敛速度也优于另两种改进进化算法.     

Metamodel-based global optimization using fuzzy clustering for design space reduction

High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strat     

轻型货车EQ1060F车身的结构优化设计研究

主要研究轻型货车 EQ1 0 6 0 F驾驶室车身结构优化设计中的一些关键问题 ,包括结构有限元分析、优化方法选择、敏度分析和结构重分析 ,选择了序列二次规划法用于结构优化问题且收敛效果较好。该研究为汽车车身设计提供了一条新的设计思路。     

轻型货车EQl060F车身的结构优化设计研究

主要研究轻型货车EQl060F驾驶室车身结构优化设计中的一些关键问题,包括结构有限元分析、优化方法选择、敏度分析和结构重分析,选择了序列二次规划法用于结构优化问题且收敛效果较好。该研究为汽车车身设计提供了一条新的设计思路。     

Multi-objective Optimization of a Parallel Ankle Rehabilitation Robot Using Modified Differential Evolution Algorithm

Dimensional synthesis is one of the most difficult issues in the field of parallel robots with actuation redundancy. To deal with the optimal design of a redundantly actuated parallel robot used for an...     

Fixed, low-order controller design with time response specifications using non-convex optimization

In this paper, we present a new algorithm for designing a fixed, low-order controller with time response specifications for a linear time invariant (LTI), single input single output (SISO) plant. For a two-parameter feedback configuration, the problem of finding a fixed or low-order controller to meet the desired time response specification is reduced to the least square estimation (LSE) in the sense of partial model matching (PMM), which minimizes a quadratic cost function. The closed-loop stability condition imposed on the controller parameters is formulated by the polynomial matrix inequality (PMI) constraint associated with the cost function. When the cascade feedback structure is considered, the zeros of the controller may be a substantial obstacle when designing a controller that has a good time response. This problem can also be formulated using polynomial constraints. Consequently, it is shown that the total problem here can be formulated as an optimization problem with a quadratic objective function and several polynomial constraints in the controller parameter space. We show that the SeDuMi with YALMIP interface [L?fberg J. YALMIP: A toolbox for modeling and optimization in MATLAB, in: Proceedings of the IEEE symposium on computer aided control systems design 2004. p. 284-9. http://control.ee.ethz.ch/~joloef/yalmip.php] can be used for solving this problem. Finally, several illustrative examples are given.     

粒子群算法在工程优化设计中的应用

将粒子群算法与惩罚函数法相结合,建构一种离散粒子群算法,解决工程上非线性约束离散变量优化设计问题。为实现离散变量与连续变量的转化,构造了相应的扩张函数,提出惩罚因子的确定策略。通过容器设计算例验证,粒子群算法方法优于文献所列方法。应用粒子群算法、惩罚函数法及所提出的策略对波纹管工程实例进行优化设计,其单位重量下整体波纹管的补偿量比在用产品提高了79.96%,与理论解接近,进一步证明了离散粒子群算法及策略在处理工程非线性约束离散优化设计问题时的有效性,其为工程上类似优化设计提供借鉴。     

Non-probabilistic Robust Optimal Design Method

For the purpose of dealing with uncertainty factors in engineering optimization problems, this paper presents a new non-probabilistic robust optimal design method based on maximum variation estimation. The method analyzes the effect of uncertain factors to objective and constraints functions, and then the maximal variations to a solution are calculated. In order to guarantee robust feasibility the maximal variations of constraints are added to original constraints as penalty term; the maximal variation of objective function is taken as a robust index to a solution; linear physical programming is used to adjust the values of quality characteristic and quality variation, and then a bi-level mathematical robust optimal model is coustructed. The method does not require presumed probability distribution of uncertain factors or continuous and differentiable of objective and constraints functions. To demonstrate the proposed method, the design of the two-bar structure acted by concentrated load is presented. In the example the robustness of the normal stress, feasibility of the total volume and the buckling stress are studied. The robust optimal design results show that in the condition of maintaining feasibility robustness, the proposed approach can obtain a robust solution which the designer is satisfied with the value of objective function and its variation.     

Unbalanced Tolerance Design and Manufacturing Setting with Asymmetrical Linear Loss Function

Taguchi has developed many loss functions, and many of the situations are approximated by the quadratic function. Using a quadratic loss function when the actual loss function is non-quadratic may cause the incorrect input parameter levels to be chosen. In certain situations, a linear loss function is more appropriate in industrial applications. If tolerance design is unbalanced, setting the process mean at the nominal will not minimise the expected quality loss. Thus, two specific models of linear loss function are discussed for unbalanced tolerance design. One is an asymmetrical linear loss function and the other is a truncated asymmetrical linear loss function. The optimal process means for these two loss functions are also compared with each other. The results show that the process mean should be shifted a little from the nominal such that the expected quality loss is minimised.     

基于灵敏度分析的稳健可靠性优化设计模型及MATLAB实现

在机械零件的可靠性优化设计中,普遍存在约束的作用,且最优解往往位子可行域的边界上。由于外界环境的变化或人为因素造成设计变量扰动,可能使设计成为不可行。本文提出了一种基于设计变量敏感度的稳键性设计方法,建立了基于灵敏度分析产生附加目标函数的两种稳健可靠性优化设计模型,并用 ＭＡＴＬＡＢ语言的优化工具箱和符号工具箱来实现机械零件的稳健可靠性优化设计,计算实例说明所述模型的可行性与实用性。     

A three-dimensional or penalty finite element method for plate bending

This paper, a sequel to an earlier paper by the same authors, uses a three dimensional or penalty function approach to obtain finite element solutions for plate bending problems. The advantage in using this approach is that the finite element subspaces need only be continuous; the disadvantages are that more functions are needed.In our previous paper, we used piecewise quadratic and linear functions, in the present paper we use piecewise cubic and quadratic functions with a resultant reduction of the discretization error. We also suggest an interpolation method or an a priori choice of the thickness to length ratio which are appropriate for thin or moderately thick plates. Numerical results are given for clamped and simply supported plates with point and distributed loads.