Dynamic multi-response optimization using principal component analysis and multiple criteria evaluation of the grey relation model

The application of parameter design methodology has been considerable in recent years to make system performance robust over a wide range of input conditions. This notion has been referred to as a robust design with dynamic characteristics. Due to product complexity, multiple correlated characteristics must be simultaneously evaluated for improving product quality. Dynamic multi-response optimization is becoming an important issue to contemporary industry. This study developed a novel procedure of optimizing dynamic multi-responses using principal component analysis (PCA) and multiple criteria evaluation of the grey relation model. PCA can consider the correlations among multiple quality characteristics to obtain uncorrelated components. These components are then substituted into multiple criteria evaluation of the grey relation model to determine the optimal factor level combination. A case study demonstrates the effectiveness of the proposed procedure for optimizing dynamic multi-response processes.     

基于多主体仿真的产品开发过程评价及优化

为研究产品开发项目的过程动态性能,提出采用基于多智能主体建模原理构建产品开发过程的仿真模型,实现了以人为中心的产品开发过程仿真。基于多主体仿真,提出反映人因、组织和过程性能的综合评价指标,包括计划偏移率、组织薪酬、过程风险和失误水平等。研究了关键评价指标的算法,并在仿真程序中加以实现。最后,以摩托车零件开发项目为例进行仿真,并从任务流、人力配置、组织结构等方面对该项目进行了过程性能优化分析。     

Prediction of coal feeding during sintering in a rotary kiln based on statistical learning in the phase space

In alumina rotary kiln production, adjusting the coal feeding rate is the main way to maintain sintering temperature stability during the sintering process, which plays a critical role in improving production quality and reducing energy consumption. In this paper, a novel integrated method (termed PSR-PCA-HMM) is proposed to predict the coal feeding state for optimal control by integrating principal component analysis (PCA) and the hidden Markov model (HMM) based on phase space reconstruction (PSR). First, the thermal signals in rotary kilns are shown to have obvious chaotic characteristics. Second, PSR is utilized to extract the features of the sintering process in a rotary kiln, and PCA is proposed to efficiently reduce the redundancy of the high-dimensional feature space reconstructed by the PSR. Then, considering the nonlinear dynamic characteristic of the sintering process, three HMM models are built to capture the nonlinear dynamic relationship between thermal variables and the corresponding coal feeding state. Finally, the posterior probabilities with respect to the three HMM models are estimated by using the forward algorithm, and the final prediction of coal feeding is determined by the maximized likelihood estimation. Based on field data, the application results indicate that the PSR-PCA-HMM method can significantly improve prediction performance and help realize stable closed-loop control for the sintering temperature.     

基于熵值法的产品广义质量综合评价方法

为有效地对产品质量做出客观评价,运用产品广义质量综合评价方法,针对不同的指标类型选用不同的从优模式进行数据标准化,结合熵值法对指标权重值进行确定,对产品质量进行综合评价.以气流筛分机为例,利用基于熵值法的产品广义质量综合评价方法对各型号的气流筛分机进行产品质量综合评价,并通过用VB编写的计算机软件对具体评价过程进行计算,使评价过程更加客观可靠.通过此方法得出的评价结果为用户合理选择产品提供了依据,为企业评价与提高产品总体质量提供科学的决策依据.     

应用人工神经网络预测加工尺寸误差的动态分布

为了有效控制机械加工工艺过程 ,保证工件加工质量 ,需要及时掌握过程尺寸分布及其变化规律。为此 ,提出一种应用人工神经网络预测加工尺寸误差动态分布的方法 ,该方法在实际应用中得到了较为满意的验证。     

基于层次分析法和熵值法的产品广义质量综合评价方法

为客观有效地评价产品质量,以产品广义质量综合评价方法为基础,结合层次分析法和熵值法对指标权重值进行综合确定,使评价过程更加科学合理,避免了不合理结果的产生.以微型家用轿车为例,从技术性、经济性和社会性三方面对其综合性能进行评定.评价结果表明,此方法得出的评价结果符合客观实际,为用户选择产品提供了科学的依据.     

基于阶跃响应的反向响应过程的预测函数控制

通过分析被控过程产生反向响应的内在机理,基于过程阶跃响应系数利用预测函数控制算法实现反向响应过程的控制。将系统控制结构归结为内模控制结构,并在此基础上给出控制系统的鲁棒稳定性证明。该方法的优点是所得控制器结构简单、参数易于调节,且所给方法也适用于其他非最小相位系统的控制。实验结果证实该方法有很强的抗干扰能力和较好鲁棒性。     

基于误差传播理论的动态测量误差灰色评定方法

动态测量是随测量时间而变化的非平稳随机过程 ,动态测量数据具有时变性、随机性、相关性和动态性四个基本特性。灰色模型实时误差预报修正的动态测量误差序列同样为随机过程 ,也具有上述基本特性。据此提出灰色模型误差预测值的评估应以误差在系统内的传播方式与程度来进行 ,并借鉴静态测量误差评定的均方差参数方法 ,推算出灰色系统均方差参数 ,作为评定误差预测值精度的方法     

应用跟踪误差等效模型评价光电经纬仪跟踪性能

针对目前光电经纬仪跟踪性能室内检测方法的缺陷,提出了评价光电经纬仪跟踪性能的新方法。基于系统辨识理论建立了光电经纬仪跟踪误差等效模型,将等效正弦信号输入等效模型,通过对模型输出进行数据处理来评价光电经纬仪的跟踪性能。介绍了建立等效模型的原理和等效模型阶次,给出了根据光电经纬仪检测指标进行等效正弦信号设计的方法。为得到精确的模型参数,采用动态靶标目标角频率连续调制模式实现了对光电经纬仪动态性能的持续激励。仿真和实验结果显示,得到的跟踪误差等效模型估计误差均值为(2.5872×10-6)°≈0°,最大值为1.8″,标准差为1.1″,表明建立的等效模型能够满足跟踪性能评价要求,实现了对光电经纬仪跟踪性能的合理、准确评价。     

Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes

In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes.     

基于PCA的多元质量控制与诊断方法研究

给出了一种基于PCA（Prinoipal Component Analysis）的多元质量控制与诊断方法;基于Matlab计算平台,给出了该方法的辅助程序实现,包括过程数据预处理、PCA模型构建、多元质量控制图、主成分单变量控制图和原始单变量控制图的绘制;提出了一种基于PCA的多元质量控制与诊断的过程模型,结合电子装配行业表面贴装工艺中焊点质量控制进行了实例研究.     

Neural network adaptive position tracking control of underactuated autonomous surface vehicle

The present study investigates the position tracking control of the underactuated autonomous surface vehicle, which is subjected to parameters uncertainties and external disturbances. In this regard, the backstepping method, neural network, dynamic surface control and the sliding mode method are employed to design an adaptive robust controller. Moreover, a Lyapunov synthesis is utilized to verify the stability of the closed-loop control system. Following innovations are highlighted in this study: (i) The derivatives of the virtual control signals are obtained through the dynamic surface control, which overcomes the computational complexities of the conventional backstepping method. (ii) The designed controller can be easily applied in practical applications with no requirement to employ the neural network and state predictors to obtain model parameters. (iii) The prediction errors are combined with position tracking errors to construct the neural network updating laws, which improves the adaptation and the tracking performance. The simulation results demonstrate the effectiveness of the proposed position tracking controller.

     

供应商参与下的产品方案多目标优化与多属性决策规划方法

针对现有供应商参与下的产品方案规划方法在零部件优化和供应商评价等两方面所存在的局限性,提出零部件多目标优化和供应商模糊动态多属性决策评价相集成的二阶段规划方法。建立以产品零部件组合方案的质量、成本和交货期等为目标的数学优化模型,以Epsilon策略和主导性约束处理机制对强度Pareto多目标进化算法进行适应性改进后用于对该优化模型进行求解并获得有限数量的Pareto最优解。引入傅里叶级数对伯努利预测模型的误差进行修正来提高预测精度,将修正的伯努利预测模型和模糊动态多属性决策模型相结合用于对Pareto最优解中包含的各零部件供应商进行评价,进而确定出各零部件的最佳供应商和最终的产品规划方案。以供应商参与下的空分设备研发过程作为实例,进行数值仿真计算,结果表明所提出方法具有可行性与有效性。     

Dynamic analysis and control strategy of wet clutches during torque phase of gear shift

Control over the clutch during gear shift is the key technique in automatic transmission shift control and this control largely decides the shift quality. The engagement of the on-coming clutch and the disengagement of the off-going clutch should be controlled synchronously and accurately to achieve a smooth shift. Optimal control of clutch torque exchange phase is required to achieve this synchronous and accurate control. Shift quality can be easily influenced with inappropriate control parameters because of the many factors that affect the torque phase, as well as the use of closed-loop control. In this study, a dynamic model of frictional clutch with electro-hydraulic shift control is built. On the basis of the study of the influence of clutch-related parameters, an optimal control model is proposed with the closed-loop control together with an adaptive control method based on micro-slip clutch control. This control method can continually self-adjust control parameters to prevent shock, improve control precision and effectively reduce the calibration work after. Test result shows that this closed loop with adaptive method ensures consistently good shift quality.     

CONVEX CONTROLLER DESIGN APPLIED TO AC INDUCTION MOTOR TO SATISFY MULTIPLE SIMULTANEOUS SPECIFICATIONS

The application of a closed-loop specification oriented feedback control design method, which addresses the design of controllers to satisfy multiple simultaneous conflicting closed-loop performance specifications is presented. The proposed approach is well suited to the design of controllers which must meet a set of conflicting performance specifications. Gain tuning is central to the design process, however, the tuning process is greatly simplified over that presented by the problem of tuning a PID controller for example. The proposed control method is applied to an AC induction motor, with an inner-loop flux vector controller applied to design a position control system. Experimental results verify the effectiveness of this method.     

A frequency-domain grinding force model-based approach to evaluate the dynamic performance of high-speed grinding machine tools

This article provides an integrated approach to evaluate grinding machine's dynamic performance in speed range by examining both the manufacturing process and the machine tool. This approach considers the dynamic grinding force as a starting point. The dynamic change of the cutting depth in the grinding process is studied first. Then, based on the dynamic model of grinding process developed in previous studies, the dynamic forces of the manufacturing process are predicted. By analyzing the grinding force model in the frequency-domain and the frequency response function, the root mean square values of the machine vibration are calculated. The evaluation works by comparing the variation and trend of the vibration level. The proposed evaluation method is then applied to a physical grinding machine. The dynamic performance obtained from the experiment matches the predicted trend in the models. In addition, this method can be used to inspect and optimize the design of the machine's spindle system. For the grinding process that requires a high dynamic performance, this method also provides reference for the speed selection within all speed range.     

Efficient decentralized iterative learning tracker for unknown sampled-data interconnected large-scale state-delay system with closed-loop decoupling property

In this paper, an efficient decentralized iterative learning tracker is proposed to improve the dynamic performance of the unknown controllable and observable sampled-data interconnected large-scale state-delay system, which consists of N multi-input multi-output (MIMO) subsystems, with the closed-loop decoupling property. The off-line observer/Kalman filter identification (OKID) method is used to obtain the decentralized linear models for subsystems in the interconnected large-scale system. In order to get over the effect of modeling error on the identified linear model of each subsystem, an improved observer with the high-gain property based on the digital redesign approach is developed to replace the observer identified by OKID. Then, the iterative learning control (ILC) scheme is integrated with the high-gain tracker design for the decentralized models. To significantly reduce the iterative learning epochs, a digital-redesign linear quadratic digital tracker with the high-gain property is proposed as the initial control input of ILC. The high-gain property controllers can suppress uncertain errors such as modeling errors, nonlinear perturbations, and external disturbances (Guo et al., 2000) [18]. Thus, the system output can quickly and accurately track the desired reference in one short time interval after all drastically-changing points of the specified reference input with the closed-loop decoupling property.     

面向多品种小批量制造过程的NAD-EWMA控制图多目标优化设计方法

针对面向多品种小批量制造过程设计质量控制图面临的样本数量少、分布不确定问题,提出一种基于非参数、自适应、动态EWMA控制图的多目标优化设计方法。基于非参数统计理论与自适应控制的思想,构建与样本数据分布无关的控制图统计量,并设计一种基于聚类距离的动态抽样方法实现样本抽样;在此基础上,考虑统计性、经济性建立控制图多目标优化设计模型,基于改进人工鱼群算法与云清晰综合评价方法实现对模型求解,进而构建面向多品种小批量制的非参数自适应动态EWMA控制图。最后,以航天复杂构件制造过程为例,对制造过程进行动态监控。结果表明,所提方法能够快速监控到质量异常,监控性能高,验证了该方法的有效性和可行性,为多品种小批量制造过程实际的质量监控提供一种有效的途径。     

基于人因仿真分析的装配序列评价模型及应用

为减少装配作业疲劳,降低动作强度,提高装配质量和效率,提出了一种基于人因工程仿真分析的装配序列综合评价模型。以装配序列的人因性能优劣为目标,创建了包含定量与定性指标在内的综合评价指标体系;提出了装配序列人因工程仿真分析模型,通过虚拟仿真技术与人因分析方法获取人因性能的基础指标属性值。采用客观自适应熵权法和改进模糊层次分析法分别确定各定量指标和定性指标的权重,利用三角模糊数定量化定性评价值,基于Topsis框架得到适合人体作业的最优装配序列。最后结合Tecnomatix数字化仿真平台将该评价模型应用于某航天产品减速器可行装配序列的优选,验证了方法的有效性。     

High-accuracy servo press system for the clinching joint process

This paper focuses on the quality improvements on clinching joints using a servo press with a Radial basis function neural network and a sliding mode (RBFS) control strategy. Bottom thickness, which is affected by the press punch position, is usually used to monitor clinching joint quality. Traditional clinching presses are driven by pneumatic pistons or motors that provide feedback on punch force or motor position. However, this feedback is indirectly related to the joint bottom thickness. Clinching workers who set the control parameters on these presses depend on tests and statistics. Thus, this paper presents a servo press system that utilizes punch position feedback to directly control the joint bottom thickness. Transmission errors are considered for the movement accuracy of the servo press. A mathematical model of the servo press is established for analyzing. An algorithm, which combines RBF neural network and sliding mode, is proposed and applied for press position tracking. This algorithm adopts an RBF neural network to approximate the nominal model of the press system. The update law of the algorithm is based on the Lyapunov function used to prove the stability of a closed-loop system. The sliding mode controller compensates for the neural network error and disturbance. Finally, experiments are executed on the servo press with an RBFS controller. To evaluate the performance of the proposed method, a fuzzy PID controller is also applied to the press for comparison. The results indicate that the servo clinching press system with RBFS efficiently and accurately control the clinching jointing process.