多目标稳健优化设计方法在车身设计制造中的应用研究

传统的稳健优化设计方法只是针对单目标响应进行的优化设计.然而,评价一个产品的质量特性应该是多方面的并且各个质量特性之间可能会发生相互冲突,因此,研究实用和高效的多目标稳健优化设计方法具有非常重要的现实意义.论文提出了采用双响应面思想分别构造出每个产品特性和约束条件的均值和方差的响应面模型,在此基础上,将质量工程中的6σ...     

Integration of uniform design and quantum-behaved particle swarm optimization to the robust design for a railway vehicle suspension system under different wheel conicities and wheel rolling radii

This paper proposes a systematic method, inte-grating the uniform design(UD)of experiments and quantum-behaved particle swarm optimization(QPSO),to solve the problem of a robust design for a railway vehicle suspension system. Based on the new nonlinear creep model derived from combining Hertz contact theory, Kalker's linear the-ory and a heuristic nonlinear creep model,the modeling and dynamic analysis of a 24 degree-of-freedom railway vehi-cle system were investigated.The Lyapunov indirect method was used to examine the effects of suspension parameters, wheel conicities and wheel rolling radii on critical hunting speeds.Generally,the critical hunting speeds of a vehicle sys-tem resulting from worn wheels with different wheel rolling radii are lower than those of a vehicle system having origi-nal wheels without different wheel rolling radii.Because of worn wheels, the critical hunting speed of a running rail-way vehicle substantially declines over the long term. For safety reasons,it is necessary to design the suspension sys-tem parameters to increase the robustness of the system and decrease the sensitive of wheel noises.By applying UD and QPSO,the nominal-the-best signal-to-noise ratio of the sys-tem was increased from?48.17 to?34.05 dB.The rate of improvement was 29.31%.This study has demonstrated that the integration of UD and QPSO can successfully reveal the optimal solution of suspension parameters for solving the robust design problem of a railway vehicle suspension sys-tem.     

基于多目标优化策略的结构可靠性稳健设计

应用可靠性稳健优化设计理论和多目标决策方法,将结构可靠性稳健优化设计转化为多目标优化问题。运用灰色理论中的关联分析法,选取粒子群算法中的全局极值和个体极值,提出了灰色粒子群算法求解可靠性稳健优化设计问题。与传统方法相比,该方法简便易行并能迅速准确地得到结构可靠性稳健优化设计信息。     

基于结构可置信性鲁棒优化算法的离散优化问题研究

传统优化设计认为问题的参数(如材料属性和外加载荷等)是确定的,并且设计变量通常是连续的.而在实际应用中产品制造和测量等存在不可避免的误差,并且工程需要的设计结果(如钢筋截面尺寸等)往往是离散的.即使对于考虑了不确定性参数影响的连续最优解,经过圆整处理后也很可能产生较大偏差甚至变得不可行.针对该难点,本文结合非概率不确定性鲁棒优化算法,建立与离散的基于圆整策略的优化算法列式等价的鲁棒优化列式及用于解决离散优化问题的可置信性鲁棒优化方法.并进一步研究了离散变量不确定性优化问题的可置信性鲁棒优化求解方法,利用非线性半定规划进行高效求解,可严格保证所得结果的可行性.本文揭示了传统离散优化思想和不确定性优化思想的内在联系,完善了优化设计理论体系,为后续相关研究提供了全新思路和示范.     

基于断面形状优化的地铁车轮减振降噪研究

以降低地铁车辆在运行中产生的轮轨接触噪声为目的,将结构动力优化方法运用于地铁车轮断面外形设计,建立了地铁车轮振动噪声最优化设计的数学模型,编制了相应的算法程序.以我国某地铁车轮为例,给出了以车轮断面外形几何参数为设计变量、车轮结构振动辐射噪声值最小为目标函数的优化计算实例,得到了车轮断面外形几何参数在可行域内的最优解.结果表明,该优化设计方法是成功的,可以有效地降低车轮因振动而产生的噪声.     

Adaptive vehicle posture and height synchronization control of active air suspension systems with multiple uncertainties

This paper addresses the tasks of height and posture motion control for an electronically controlled active air suspension (AAS) system. A mathematical model of a vehicle body with AAS system is established to describe the dynamic characteristics and then formulated into a multi-input multi-output nonlinear system by considering parametric uncertainties and unmodelled dynamics. Based on this mathematical model, a synchronization control strategy is proposed to adjust the heights of adjacent AASs simultaneously, driving the pitch and roll angles closely to an arbitrarily neighborhood of zero, achieving global uniform ultimate boundedness. The proposed controller is robust to parametric uncertainties and external disturbances. A projection operator is utilized to limit the estimated parameters to their corresponding prescribed bounds in finite time. A co-simulation is conducted by combining a virtual vehicle plant with ASS system in AMEsim with the proposed synchronization controller in MATLAB/Simulink. Simulation results demonstrate that the proposed synchronization controller is effective and robust.     

Design of neural network-based control systems for active steering system

Nowadays, safety of road vehicles is an important issue due to the increasing road vehicle accidents. Passive safety system of the passenger vehicle is to minimize the damage to the driver and passenger of a road vehicle during an accident. Whereas an active steering system is to improve the response of the vehicle to the driver inputs even in adverse situations and thus avoid accidents. This paper presents a neural network-based robust control system design for the active steering system. Primarily, double-pinion steering system used modeling of the active steering system. Then four control structures are used to control prescribed random trajectories of the active steering system. These control structures are as classical PID Controller, Model-Based Neural Network Controller, Neural Network Predictive Controller and Robust Neural Network Predictive Control System. The results of the simulation showed that the proposed neural network-based robust control system had superior performance in adapting to large random disturbances.     

Robust trajectory tracking control for a laboratory helicopter

This paper presents a robust nonlinear control strategy to deal with the trajectory tracking control problem for a laboratory helicopter. The helicopter model is considered as a nominal one with uncertainties such as unmodeled nonlinear dynamics, parametric uncertainties, and external disturbances. The proposed control approach incorporates the feedback linearization technique (FLT) and the signal compensation technique. The FLT is first applied to achieve the linearization of the nominal nonlinear model for reducing the conservation of the robust compensator design. A nominal controller based on the linear quadratic regulation method is designed for the linearized nominal system, whereas a robust compensator is introduced to restrain the influences of the uncertainties. It is shown that the trajectory tracking errors of the closed-loop system are ultimately bounded, and the boundaries can be specified by choosing the controller parameters. Simulation and experimental results on the lab helicopter verify the effectiveness of the proposed method.     

Non-probabilistic reliability method and reliability-based optimal LQR design for vibration control of structures with uncertain-but-bounded parameters

Uncertainty is inherent and unavoidable in almost all engineering systems. It is of essential significance to deal with uncertainties by means of reliability approach and to achieve a reasonable balance between reliability against uncertainties and system performance in the control design of uncertain systems. Nevertheless, reliability methods which can be used directly for analysis and synthesis of active control of structures in the presence of uncertainties remain to be developed, especially in non-probabilistic uncertainty situations. In the present paper, the issue of vibration con- trol of uncertain structures using linear quadratic regulator （LQR） approach is studied from the viewpoint of reliabil- ity. An efficient non-probabilistic robust reliability method for LQR-based static output feedback robust control of un- certain structures is presented by treating bounded uncertain parameters as interval variables. The optimal vibration con- troller design for uncertain structures is carried out by solv- ing a robust reliability-based optimization problem with the objective to minimize the quadratic performance index. The controller obtained may possess optimum performance un- der the condition that the controlled structure is robustly re- liable with respect to admissible uncertainties. The proposed method provides an essential basis for achieving a balance between robustness and performance in controller design ot uncertain structures. The presented formulations are in the framework of linear matrix inequality and can be carried out conveniently. Two numerical examples are provided to illustrate the effectiveness and feasibility of the present method.     

基于可靠性的车辆防护组件优化

在传统的优化流程中,不考虑设计变量的不确定性将引起设计目标的性能波动,甚至设计失败。为提高军用车辆底部防护能力,针对一种车辆防护组件进行了可靠性优化。在爆炸防护优化中引入多目标可靠性优化,通过实验设计和灵敏度分析筛选设计变量,再构建并选择准确度最高的代理模型,运用多目标遗传算法完成防护组件的可靠性优化。实验和数值模拟结果表明,优化后的防护组件满足防护性和轻量化的要求,且设计的可靠性得到了提升,可为后续防护组件设计生产提供参考。     

拉延成形多目标序列响应面法优化设计方法

为了克服常规响应面法在整个设计空间进行逼近导致精度低和传统的单目标优化设计,只能针对其中的一个目标进行优化的缺陷,提出了一种多目标序列响应面法,优化设计拉延筋几何参数的方法. 该方法通过移动、缩放等方式在设计空间中不断更新兴趣域,在不同的兴趣域中将实验设计、响应面法和多目标粒子群优化算法相结合,获得了一组最小化起皱、拉裂缺陷的等效拉延阻力非劣解. 利用最小距离选解法从非劣解集中挑选出一组成形效果最好的解, 并以此解作为下一迭代步兴趣域的中心,直到收敛至一组最优的等效拉延约束阻力. 以最优等效拉延阻力为约束条件,利用等效拉延筋阻力模型结合遗传算法对拉延筋的真实几何参数进行设计. 优化设计的拉延筋几何参数提高了板料的成形性能. 算例表明,该方法具有较高的精度和较强的工程实用性.      

Robust optimization of the non-linear behaviour of a vibrating system

In this paper, one proposes to optimize the vibratory behaviour of an absorber of vibration related to a system subjected to a harmonic load, in the presence of uncertainties on the design parameters. The total system is modeled by two degrees of freedom (2 dof) with a shock absorber and a generalized non-linear stiffness. The resolution is carried out in the temporal field according to a traditional diagram.Two cases of non-linearity were considered. In the first case, one is interested in the study of the system comprising a combination of the two generalized non-linearities of quadratic and cubic type of stiffness and damping. The second case relates to a non-linearity of non-whole power (in this paper 1.5), combined with the cubic case. It is a question of seeking the optimal responses envelopes of the deterministic and stochastic case and this for the non-linear displacements, phases and forces.The multi-objective optimization step consists in seeking the first Pareto front of several linear and non-linear objective functions by using a genetic algorithm of type “NSGA” (Non-dominated Sorting Genetic Algorithm).The design parameters are: mass, linear and non-linear stiffness and damping of the absorber. To obtain solutions presenting a good compromise between optimality and the robustness, one introduces uncertainties on these design parameters. The robustness is then defined by the dispersion of the parameters (definite as the ratio: mean value/standard deviation) and it is introduced as additional objective function.The use of the clusters resulting from the Self-Organizing Maps of Kohonen (SOM) is also suggested for a rational management of the design space. A study of sensitivity a posteriori can be exploited in order to eliminate the non-significant design parameters.     

多工况下结构鲁棒性拓扑优化设计

针对工程中存在多个随机不确定工况载荷作用的情况, 将鲁棒性设计思想引入到连续体结构拓扑优化设计, 发展和完善不确定性优化理论和计算方法. 基于概率模型和SIMP方法,提出以结构柔顺度标准差最小化为目标、具有体积约束的连续体鲁棒性拓扑优化数学模型.通过对目标函数及其灵敏度计算公式的推导, 采用数学规划法实现优化问题的求解. 数值算例验证了所提优化模型的正确性及算法的有效性, 并通过与确定性优化结果的比较,证明鲁棒性拓扑优化能够给出结构柔顺性变异更小的材料分布.      

Evolutionary algorithm-based PID controller tuning for nonlinear quarter-car electrohydraulic vehicle suspensions

The basic challenge associated with the design of vehicle suspension system is the attainment of an optimal trade-off between the various design objectives. This study presents the design of proportional-integral-derivative (PID) controller for a quarter-car active vehicle suspension system (AVSS) using evolutionary algorithms (EA) such as the particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE). Each of the EA-based PID controllers showed overall improvement in suspension travel, ride comfort, settling time and road holding from the manually tuned controller and the passive vehicle suspension system. These improvements were, however, achieved at the cost of increased actuator force, power consumption and spool-valve displacement. DE-optimized PID control resulted in the best minimized suspension performance, followed by the GA and PSO, respectively. Frequency-domain analysis showed that all the signals were attenuated within the whole body vibration frequency range and the EA-optimized controllers had RMS frequency weighted body acceleration of the vehicle within allowable limits for vibration exposure. Robustness analysis of the DE-optimized PID-controlled AVSS to model uncertainties is carried out in the form of variation in vehicle sprung mass loading, tyre stiffness and speed.     

近空间高速飞行器气动特性研究与布局设计优化

高空高速飞行中的黏性干扰效应、真实气体效应和稀薄气体效应成为决定未来空天飞行器能否实现安全飞行、精确控制和制导的重大基础科学问题.介绍了黏性干扰效应、真实气体效应和稀薄气体效应对高空高速飞行器气动特性影响,回顾了飞行器气动布局设计优化的发展过程,给出典型高速高升阻比飞行器气动布局设计及优化的结果.      

Multi-objective traction optimization of vehicles in loose dry sand using the generalized reduced gradient method

A work optimization strategy is combined with algorithms within the vehicle-terrain interface (VTI) model to maximize the traction of a four-wheel vehicle operating on loose dry sand. The optimization model distributes traction among the steered and non-steered wheels with the work optimum coefficient (WOC) of each wheel treated as an independent design objective. Drawbar pull (DBP), motion resistance (MR), longitudinal traction coefficient (LTC), lateral force coefficient (LFC), tire deflection, and wheel slip are key parameters that appear in the VTI model for traction performance analysis. The analysis includes wheels of different diameters, widths, heights, and inflation pressures, under variable wheel slips. A multi-objective optimization problem is formulated over a thirteen-dimensional search space bounded by eight design constraints. The generalized reduced gradient method is used to predict optimal values of the design variables as well as ground and traction parameters such as DBP, MR, LTC, and LFC for maximum slope climbing efficiency. The WOCs are maximized for lateral slip angles between 0° and 24° to find a set of Pareto optimal solutions over a wide range of weight factors. A method to apply the optimization results for predicting vehicle performance and traction control on dry sand is presented and discussed.     

铁路车辆/轨道耦合系统在竖向冲击载荷作用下动态响应的计算机模拟研究

车辆与轨道的动态相互作用,是铁路轮轨接触式运输系统中最基本的问题之一,它直接制约着铁路运营速度的提高和运载重量的增加,也影响着铁路安全运行。本文采用有限元方法,对我国C61型运煤货车,按照车辆/轨道系统的实际几何形状、材料性质和边界条件建立了包括车辆和轨道系统的有限元模型,应用大型非线性动力分析程序LS-DYNA3D来模拟车辆通过轨道错牙接头时的轮/轨动态响应过程。计算结果表明车轮和轨道之间的竖向动态接触力大约是静轮载的2倍,与已有的现场试验结果基本吻合。因此应用有限元方法研究车辆/轨道耦合系统是可行和可靠的。     

天线结构多目标模糊优化设计

本文在结构模糊优化设计理论的最新成果——普遍型模糊优化的基础上研究解决了包括重量、精度、动力基频和安全度等目标在内的天线结构多目标模糊优化设计问题,使得天线结构优化更令面、更合理、更实际。这是在计算机上对多变量、多工况、多约束、多目标大型结构进行模糊优化设计的成功应用的实践。     

基于拓扑优化的车辆底部防护组件改进设计

为提升车辆底部防护组件的抗爆性能,降低车身底板变形对车内乘员的威胁,基于混合自动元胞机法对防护组件中的加强梁进行拓扑优化设计,得到了加强梁的最佳材料分布形式,随后根据拓扑优化结果进行了工程诠释和重新设计。为了进一步提升防护组件的抗爆性能,采用多目标优化的方法对加强梁进行优化设计,以基板的挠度峰值、基板的最大动能和防护组件质量为优化目标,防护组件的质量为约束条件,以及梁的厚度、截面尺寸为设计变量,得出加强梁各参数组合的最优方案。结果表明,相比于初始设计,该方案在不增加结构质量的情况下,防护组件的抗爆性能得到显著提升,改进后基板的挠度峰值降低了5%,基板的最大动能降低了11.58%。     

基于概率和非概率混合模型的结构鲁棒设计方法

讨论了同时存在概率不确定性量和非概率不确定性量时可行鲁棒性和目标函数鲁棒性的实现策略,提出了基于概率和非概率混合模型的结构鲁棒设计方法。基本做法是首先视非概率型不确定性量为参变量,按照传统概率统计的方法计算约束函数和目标函数的均值和标准方差,然后再考虑非概率型不确定性量的波动变化对约束函数和目标函数统计特征量的影响,以修正常规可行鲁棒性和目标函数鲁棒性的数学模型。所提方法应用于一个10杆桁架结构的最轻质量设计和节点位移鲁棒设计,获得了对不确定性量波动变化不敏感的设计方案。