运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补

为满足工业机器人高精度复杂曲线运动的需求,本文提出运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补算法.首先,根据轨迹最大轮廓误差和机器人动力学特性对曲线分段.随后,提出优化回溯算法,使各子曲线段均可用S曲线加减速规划.之后,为保证机器人在进给速度极小值处不超速,将各加减速阶段运行时间调整为插补周期的整数倍,并对子曲线段衔接处速度平滑处理.最后,提出模型迭代寻优曲线插补,大大降低了速度波动率.仿真试验表明,该方法插补轨迹的各项指标均满足要求且最大速度波动率仅为0.000099%.真机试验也验证了该方法可有效减小轨迹误差.     

开闭件声腔对噪声传递函数分析的影响

为了准确地仿真分析汽车的NVH特性,通常需要准确获取声腔的声学特性参数。以某内饰车身为研究对象,以车内声学特性机理为基础,为探索开闭件声腔模型对噪声传递函数仿真分析的影响,分别建立了传统车内声腔模型的声固耦合系统和附加开闭件声腔的车内声固耦合系统。采用以声腔模态分析、板件贡献量分析、原点动刚度分析三种CAE仿真分析方法并结合所选车型的仿真NTF曲线特点,有针对性地分析了开闭件声腔在声腔建模时需要被考虑的原因。并通过试验验证了模型的准确性和方法的有效性。结果表明,附加开闭件声腔的建模仿真更接近实际情况,使得仿真更准确。     

汽车行驶稳定性动力学优化控制仿真研究

汽车行驶稳定动力学优化控制,旨在通过确定汽车行驶状态下纵向车速、横摆角速度、质心侧偏角等重要的状态变量,提前预知汽车未来时刻的可能的行驶状态,并将其输送到汽车底盘主动控制系统,实现动力学优化控制,提高汽车的主动安全性,减少道路交通事故.寻找一种低成本、高精度且能够实时获得车辆重要状态参数的方法,是汽车稳定行驶动力学优化控制的关键技术之一.利用Madab/Simulink仿真工具,分别建立了汽车动力学仿真模型和车辆行驶状态Kalman滤波估计仿真模型,可以同时实现对车辆行驶状态的仿真和对车辆行驶过程中横摆角速度、侧向加速度和质心侧偏角的估计,并且模型具有可扩展性.最后进行了实车场地试验,完成了阶跃曲线、双移线等操作,通过模型仿真、试验数据和状态估计结果的比较得出,三者一致性较好,同时验证了车辆动力学仿真模型和状态估计算法仿真模型的有效性和通用性.     

基于外场试验的内场仿真模型一体化验证方法

目前外场试验数据的模型验证仅完成试验数据对于仿真模型的验证,却没有考虑到模型验证对于外场鉴定试验的要求,对外场武器装备性能指标考核问题,为了通过模型验证来优化外场试验方案,提出了内场仿真模型一体化验证的概念.应用模型一体化验证思想结合外场试验特点建立了适用于装备试验鉴定领域的模型一体化验证过程模型,进行建模与仿真,并提供了一体化验证过程各步骤所使用的具体方法.上述模型一体化验证的理论与方法已成功地在潜艇试验鉴定仿真系统的模型验证过程中使用,收到了良好的应用效果.     

基于转矩分配函数的开关磁阻电机的效率优化方法

开关磁阻电机使用传统的转矩分配函数(TSF)控制时虽然可以起到一定的抑制转矩脉动的作用,但却由于换相阶段电流峰值过高,电流可控性下降等问题使得其在换相阶段出现较为明显的转矩脉动,以及较高的铜耗。针对这一问题,提出了一种基于TSF的开关磁阻电机的效率优化方法。将电机特性作为约束条件,以铜耗为优化目标建立最优化模型,利用多重嵌套的遗传算法将该最优化模型应用于Simulink仿真中,得到不同参数下最优的电流参考曲线。再根据不同转速下对电机性能的需求,进一步筛选权重参数,从而得到最优的电流参考曲线。仿真和实验结果表明,该方法能够有效地降低换相阶段的电流峰值、降低电流控制难度,进而在较低转速下抑制转矩脉动、在较高转速下提高效率。     

汽车进气系统声学模态仿真和试验

针对汽车进气系统噪声对整车NVH性能有较大影响的问题,通过与理论解的对比验证直管声学模态的仿真方法和试验方法的可行性.对进气系统进行声学模态CAE仿真,并设计一系列试验,逐级排查出CAE仿真与试验有差距的原因.根据算例的声学模态分析结果对进气系统消声元件位置的确定给出建议.     

基于闭塞区间的高速列车运行时间与节能协同优化方法

提出了一种高速列车运行时间与节能协同优化方法.针对由动态调度层、优化控制层、跟踪控制层组成的列车运行控制与动态调度一体化结构,设计了面向动态调度层和优化控制层的列车运行时间调整策略和节能速度位置曲线.基于高速铁路闭塞区间,建立了列车区间模型和列车速度曲线节能优化模型.利用模型预测控制方法对列车区间运行时间进行调整,优化列车总延误时间;根据调整后的区间运行时间设计列车运行优化速度位置曲线,减少列车运行能耗.仿真算例验证了设计的运行时间与节能协同优化策略的有效性.     

摩托车整车性能仿真系统的研究

研究摩托车整车的动特性问题,为了研究摩托车在实际道路工况下的整车性能,为了保证行驶的稳定性,建立了模拟驾驶的摩托车整车性能试验的动态系统模型.针对目前研究方法存在的"控制性能差"等问题,利用发动机台架试验数据,采用曲面拟合方法,建立发动机稳态数学模型,根据行驶动力学方程和其非线性特点,应用分段线性化方法,分别建立了道路负载模型和整车速度模型,设计模糊控制器和 PID 控制器,仿真整车驾驶.通过计算机仿真完成摩托车整车性能试验,得到在目标车速下的车速、油门开度和发动机响应曲线.为验证整个系统模型的正确性,进行结果对比和仿真分析,表明提出仿真模型是正确的,可保证各种工况下的稳定运行.     

考虑随机不确定性的常态仿真模型确认试验设计

模型确认试验是一种新的试验,其目的在于度量仿真模型的可信度.为了得到低成本、高可信度的模型确认试验方案,提出一种随机不确定性模型确认试验设计方法.首先,基于面积确认度量指标提出一种新的无量纲的模型确认度量指标(面积确认度量指标因子),并且在其基础上发展了基于专家系统的仿真模型准确性定性评判准则;然后,建立随机不确定性模型确认试验优化设计模型,提出该优化模型的求解方法;最后,通过两个数值算例对提出的模型确认试验设计方法进行验证.结果表明,小样本情况下,试验方案的随机性会影响模型评判结果的可信度;面积度量指标因子随试验样本数量的增加而收敛;随机不确定性模型确认试验设计方法能够避免试验方案对模型确认结果的影响.     

车辆开发过程中驾驶质量的客观评价及优化

针对整车驾驶质量开发中主观评价体系的不足,引入驾驶质量客观评价指标体系。明确驾驶质量开发的客观指标概念和目标曲线,以某款双离合变速器（dual cluth transmission, DCT)车型为研究对象,建立整车驾驶质量仿真模型,对爬坡度、加速度峰值、加速度增益进行分析,并通过优化车辆加速踏板扭矩策略和变速器换挡策略,使客观指标达到整车开发驾驶质量目标。整车驾驶性主观评价试验结果表明整车驾驶性满足开发目标要求,验证客观评价方法的可行性。     

Design of delta–sigma modulators via generalized Kalman–Yakubovich–Popov lemma

This paper is concerned with the design of delta–sigma modulators via the generalized Kalman–Yakubovich–Popov lemma. The shaped noise transfer function (NTF) is assumed to have infinite impulse response, and the optimization objective is minimizing the maximum magnitude of the NTF over the signal frequency band. By virtue of the GKYP lemma, the optimization of an NTF is converted into a minimization problem subject to quadratic matrix inequalities, and then an iterative algorithm is proposed to solve this alternative minimization problem. Each iteration of the algorithm contains linear matrix inequality constraints only and can be effectively solved by the existing numerical software packages. Moreover, specifications on the NTF zeros are also integrated in the design method. A design example demonstrates that the proposed design method has an advantage over the benchmark one in improving the signal-to-noise ratio.     

PIAnO在白车身轻量化设计上的应用

以某SUV车型的白车身为研究对象,采用高效的实验设计和优化软件PIAnO,综合考虑其模态、刚度、40%偏置碰和侧碰等性能进行轻量化设计。确定并优化设计变量,对白车身刚度和模态性能进行近似建模。提出分段优化方案并进行仿真验证,得到的白车身质量减少11.93 kg,下降3.08%。将该轻量化白车身的100%正碰、强度、IPI和NTF性能进行验证,满足设计要求,证明基于PIAnO的白车身轻量化策略行之有效。     

雷达装备测试性设计优化技术

针对雷达装备测试性优化设计的实际技术需求,对雷达测试性优化设计过程进行了分析。以雷达装备各阶段数据为基础,综合考虑测试效能、测试代价、可靠性约束等要素,研究了基于测试代价和测试效能的测试性优化方法,并给出了基于最小测试代价的雷达系统测试性优化模型。针对模型多目标优化求解问题,给出了一种基于改进的粒子群优化算法。该算法引入混沌理论,使初始种群呈现多样性,避免了传统粒子群算法的早熟现象,同时提高了搜索的精度和速度。通过对案例的仿真与验证表明,利用这种改进的粒子群算法对基于最小测试代价的测试性优化模型进行求解时,能够在满足模型目标函数的约束条件下,获得全局最优解。     

An approximate optimization strategy using refined hybrid metamodel

An approximate model called metamodel or surrogate model is a mathematical model that numerically approximates response of a system during an engineering simulation process or test. The introduction of a metamodel makes it possible to express response defined in the design problem as a simple mathematical function of design variables. A metamodel can be built with response surface method (RSM), kriging, neural network, radial basis function, and so on. Each method has its advantages and disadvantages. A combined metamodel called hybrid model, ensemble model, or multiple surrogates has been developed to maximize each metamodel's strength. The hybrid model of this research includes RSM and kriging. Besides, a strategy to refine the hybrid metamodel is implemented by reducing design space. In this process, information related to Hessian is utilized for an unconstrained optimization problem, on the contrary feasibility for a constrained optimization problem. This research presents a new hybrid metamodel-based optimization strategy called refined hybrid metamodel. Five mathematical test problems, two-bar design, spring design, and propeller shaft design problems are solved with the suggested method, verifying its usefulness. Most of the optimal results with the proposed method are closer to exact solutions with smaller function evaluations than existing methods.     

肺癌呼吸气体检测系统的气室设计

基于卟啉传感器阵列(PSA)的肺癌呼吸气体检测系统是通过采集处理PSA芯片表面图谱信息来对人体呼吸气体进行定性检测,达到早期肺癌诊断的目的。检测过程中,PSA芯片能否与气体分子快速、均匀结合将直接影响气体检测系统的准确度。以系统中PSA芯片与肺癌呼吸气体反应的气室为研究对象,借助CFD专用软件FLUENT对气室进行流场仿真结构优化,在气室理论模型的基础上,进行了气室实物制作,结果表明:通过采用抛物线形气室内腔、安装导流板、减小分流孔通径、适当加大分流孔倾斜角度等优化方案后,气室内呼吸气体呈层流流动状态,流场更加均匀、密集,能达到检测系统中PSA芯片与呼吸气体分子快速、均匀结合的要求。     

Decreasing Test Qualification Time in AMS and RF Systems

The authors of this article illustrate a means to use design models and simulation testbenches to decrease manufacturing test costs. This technique enables test cost optimization early in the RFIC design phase. In this article, we propose a test set optimization and qualification method that targets test application time, cost, and quality while also decreasing the generation time of production tests. Our approach decreases the manufacturing test cost of AMS and RF SoCs by automatically qualifying and optimizing existing test sets. We present a computer-aided test (CAT) tool, Plasma (platform for system qualification with mixed and analog signals), that uses fault injection and a fault simulation technique to perform test qualification and generation. This tool reduces both test time and test equipment cost using a high-level fault model. Our approach relies on the qualification and optimization of a predefined test set. With this article, we show how to reduce the test optimization time by using behavioral modeling and decreasing the number of simulated circuits. This method reduces the number of simulated fault-free models, thanks to a normal estimation.     

Multifunctional design of heterogeneous cellular structures

Mesoscale cellular structures with different desired physical properties are promising for a broad spectrum of applications. The availability of Additive Manufacturing (AM) technology has significantly relaxed the fabricating limitation of cellular structures. It enables the design of cellular structure with complex cell topologies and relative density distribution. In this paper, a multifunctional design method for heterogeneous cellular structures is proposed. To introduce this method, Function-Performance-Property-Design parameter model is proposed at first. This proposed model can help designers to analyze the complex relations between focused functions and their related design parameters. Based on the proposed F-P-P-D model, the template of compromise Decision Support Problem (DSP) is applied to generate the optimization formulation which can generally consider the performances defined for several different functions. To solve the defined optimization problem, a multifunctional design simulation infrastructure is proposed for the designed heterogeneous cellular structures. Based on this simulation infrastructure, both the value of the objective function and its gradients can be evaluated. Then, Sequential Quadratic Programming (SQP) solver can be applied to solve the defined optimization formulation. The optimal relative density of cellular structures can be achieved and converted to the heterogeneous cellular structures at the end. A case study is provided at the end of this paper. For this case study, two different cell topologies and several different combinations of optimization parameters are used. A brief discussion is made to conclude the effects of cell topologies and other optimization parameters on the optimization results. Generally, the result of this design case validates the efficiency of the proposed design method. This method provides a useful design tool for users to take advantage of heterogeneous cellular structures for multifunctional purposes.     

云模型的布谷鸟搜索算法*

针对布谷鸟搜索算法(CS)存在的不足,优化布谷鸟搜索算法求解连续函数问题的性能,结合云模型在定性与定量之间相互转换的优良特性,设计出云模型的布谷鸟搜索算法(CCS)。其核心思想是通过云模型实现布谷鸟的进化学习过程,类似差分进化进行群体间的信息交流。经过10个测试函数的实验仿真,测试结果表明该文算法能有效改善求解连续函数优化问题的性能。同时,针对连续函数优化问题,该算法与其它算法相比是有更好性能的优化算法。     

Optimal topology design of internal stiffeners for machine pedestal structures using biological branching phenomena

Naturally evolved biological structures exhibit the optimal characteristics of light weight, high stiffness, and high strength. Based on the growth mechanism of biological branch systems in nature, an optimization method for internal stiffener plate distribution in box structures is suggested. Under the given load and support conditions, the internal stiffener plates of machine pedestal structures grow, bifurcate, and degenerate towards the direction of maximum overall structural stiffness in accordance with the adaptive growth law. The optimal and distinct distribution of internal stiffener plates with the most effective load path is thus obtained. Based on this, a size optimization for lightweight design is conducted, in which the self-weight of the structures is taken as the design objective, and the natural vibration frequency and static stiffness in the direction that is sensitive to machining accuracy are set as constraints. Finally, an optimized structure is obtained. The effectiveness of the proposed method is verified by using a precision grinder bed as an example. The results of numerical simulation and 3D–printed model experiment indicate that both the dynamic and the static performance of the optimized structure are improved, while the structural weight is reduced by compared with the initial structure. The suggested design method provides a new solution approach for the design optimization of machine pedestal structures.