An integrated fuzzy approach for the selection of manufacturing technologies

In this paper, an integrated decision support system is developed, which employs fuzzy techniques to assist decision-makers in choosing an optimal solution from alternative manufacturing options in an uncertain environment. The integrated approach incorporates different justification methods (e.g., strategic, economic, and analytic evaluations) for assessing tangible benefits, like cost, and intangible benefits, like quality, of different alternatives by a fuzzy multi-criteria decision-making method. As an illustrative example, selection of different advanced manufacturing technologies has been demonstrated by using the proposed methodology. The proposed concept will greatly reduce conflicts between tangible and intangible factors, and enhance the process of identification, interpretation, and diagnosis of the value of complex manufacturing and engineering systems.     

模糊自适应预测控制在航空发动机中的应用研究

对于航空发动机这样复杂的系统,其数学模型具有较大的不确定性,而模糊控制对于解决模型不确定性问题具有较好的优势,运用模糊控制理论就具有较好的实践意义。而且,航空发动机在实际运行中存在诸多可测与不可测的扰动,将模糊建模技术与预测控制算法相结合,采用输出误差反馈启发校正的方法,有效地降低了系统设计与实现的复杂性,提高了系统的实时性,并使得该算法的模糊预测控制在鲁棒性、动态性能等方面皆优于常规PID控制。最后,通过数字仿真,对比了经典PID控制和运用模糊自适应预测控制。仿真结果表明,文中所采用的方法有较好的效果,其证明了该方法在航空发动机控制中应用的可能性。     

Spindle vibration suppression for advanced milling process by using self-tuning feedback control

The goal of this work is to concurrently counterbalance the dynamic cutting force and regulate the spindle position deviation under various milling conditions by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm, and an adaptive self-tuning feedback loop. The experimental data, either for idle or cutting, are utilized to establish the database of milling dynamics so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm as the cutting mission is engaged. Based on the estimated milling system model and preset operation conditions, i.e., spindle speed, cut depth, and feed rate, the current cutting force can be numerically estimated. Once the current cutting force can be real time estimated, the corresponding compensation force can be exerted by the equipped AMB to counterbalance the cutting force, in addition to the spindle position regulation by feedback of spindle position. At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.     

Adaptive complementary filter using fuzzy logic and simultaneous perturbation stochastic approximation algorithm

This paper addresses the problem of attitude estimation using low cost, small-sized inertial sensors under dynamic maneuvers. An adaptive complementary filter with fuzzy logic and simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed. By recognizing the situation of dynamic condition via fuzzy logic, the cut-off frequency of the complementary filter is determined adaptively under varying vehicle dynamics. Also, the SPSA algorithm is used to tune the parameters of fuzzy system. Simulation results based on the test data show that the proposed SPSA-based fuzzy complementary filter exhibits a significant performance improvement for attitude estimation during dynamic maneuvers.     

模糊逻辑在故障诊断中的应用

本文首先简述了有关模糊逻辑的概念,然后介绍一种适合模糊诊断思维的数学模型,并且给出一个通用的诊断算法;第一步,部分现象的诊断,即提出假设;第二步,逼近或排除;第三步,确定故障.最后做了一个滚动轴承故障诊断试验,结果验证了该方法的有效性.     

基于模糊逻辑的AFS／DYC集成控制策略研究

文中所研究的汽车动态控制系统是基于模糊逻辑控制的主动前轮转向（AFS）和直接横摆力矩控制（DYC）的集成。控制系统采用分层控制。上层使用模糊逻辑控制器（横摆角速度控制器）,输入为横摆角速度偏差及其变化率,其输出为直接横摆力矩控制信号和前轮修正转向角;下层（模糊集成控制器）设计了基于轮胎侧向力工作区的模糊逻辑控制器,通过调整前轮侧向力的方向,激活切换函数来调节模糊逻辑控制器的比例因子。仿真结果表明,使用非线性七自由度车辆模型,与单独的AFS或DYC控制器相比较,使用集成AFS／DYC控制系统,汽车操纵稳定性得到了很大的改善。     

能量可再生的新型汽车半主动悬架系统研究

介绍了一种采用功率电传方式的作动器,提出了基于EHA的可能量再生的新型汽车半主动悬架样机结构。同时,建立了1/4汽车半主动悬架动力学模型,设计了用于EHA半主动悬架系统的模糊控制器和天棚控制算法,并进行了仿真试验研究。结果表明,基于EHA的半主动悬架采用模糊控制方法能够兼顾不同频率路面以及有效降低车体加速度、悬架动挠度、轮胎动载荷,从而提高了汽车的乘坐舒适性和操纵稳定性。     

模糊推理自整定PID控制及其在PROFIBUS控制器中的应用

常规PID控制不能很好地适应非线性系统。将模糊控制和常规PID控制两种设计思想融合起来，提出了一种新型的模糊PID控制方法，通过建立模糊规则和进行模糊推理来确定PID控制参数，并将其应用于设计PROFIBUS-DP智能控制器。在系统运行过程中，运用模糊推理在线调整PID参数，使被控过程具有较高的控制品质，能够满足工业现场对响应速度、动态性能和稳态误差的高要求。     

模糊逻辑控制器应用于四辊冷轧机液压弯辊系统的研究

为实现四辊冷轧机液压弯辊系统的精确控制，设计应用于一种模糊逻辑控制器。仿真结果表明，模糊控制是对液压弯辊进行控制的有效工具，大大提高了液压弯辊系统的动态响应速度及对目标辊力给定值的跟踪精度。     

Controlling the navigation of automatic guided vehicle (AGV) using integrated fuzzy logic controller with programmable logic controller (IFLPLC)—stage 1

Material handling in manufacturing systems is becoming easier as the automated machine technology is improved. Nowadays, most of the research aims at increasing the flexibility and improving the performance of the automatic guided vehicle (AGV). In this paper, designed and made AGV in the Industrial Control Laboratory in Royce Lab at the University of Manchester Institute of Science and Technology will be presented. For controlling the navigation of the AGV, a newly developed controller integrated fuzzy logic with programmable logic controller will be used. By using integrated fuzzy logic controller with programmable logic controller (IFLPLC), the flexibility of AGV will be increased and we achieved great advantages, which can be used in future. Since this AGV uses programmable logic controller and fuzzy logic controllers together, then it will be useful for factories which implement flexible manufacturing system (FMS). Online maintenance and sending the commands to other machines from AGV and so on are the advantages that can be used in FMS. The aim of this paper is to propose the practical example of IFLPLC. The designed AGV is able to reach the target. Further researches are required for collision avoidance and selecting the best way in FMS     

Development of a fuzzy FMEA based product design system

The demand for high-quality and low-cost products with short development time in the dynamic global market has forced researchers and industries to focus on various effective product development strategies. The authors are carrying out research studies to explore the applicability of fuzzy logic and knowledge-based systems technologies to today’s competitive product design and development, with an emphasis on the design of high quality products at the conceptual design stage. A framework of a fuzzy FMEA (failure modes and rffects analysis) based evaluation approach for new product concepts is proposed in this paper. Based on the proposed approach and methodologies, a prototype system named EPDS-1, which can assist inexperienced users to perform FMEA analysis for quality and reliability improvement, alternative design evaluation, materials selection, and cost assessment, thus helping to enhance robustness of new products at the conceptual design stage. This paper presents the underlying concepts of the development and shows the practical application with the prototype system with a case study.     

机器人关节摩擦的自适应模糊补偿建模与控制

采用自适应模糊系统在线逼近摩擦模型并将模型辨识结果作为控制算法的补偿项，在控制方法上，采用了基于自适应模糊补偿的PD算法。在系统证明上，从李雅普诺夫函数中导出了自适应参数并且分析了闭环系统跟踪误差的有界性。在算法实现上，利用Matlab对文中的方法及证明的有效性进行了验证。     

Development and comparison of integrated dynamics control systems with fuzzy logic control and sliding mode control

In this study, four integrated dynamics control (IDC) systems abbreviated as IDCB, IDCS, IDCF, and IDCR are developed, evaluated and compared. IDC systems were integrated with brake and steer control systems to enhance lateral stability and handling performance. To construct the IDC systems, a vehicle model with fourteen degrees of freedom, a fuzzy logic controller, and a sliding mode ABS controller were used. They were tested with various steering inputs when excessive full brake pressure or no brake pressure was applied on dry asphalt, wet asphalt, a snow-covered paved road, and a split-μ road. The results showed that an IDC-equipped vehicle improved lateral stability and controllability in every driving condition compared to an ABS-equipped vehicle. Under all road conditions, IDC controllers enabled the yaw rate to follow the reference yaw rate almost perfectly and reduced the body slip angle. On a split-road, IDCB, IDCS, IDCF, and IDCR vehicles drove straight ahead with only very small deviations.     

电动助力转向与主动悬架集成系统动态性能智能控制

针对汽车电动助力转向与主动悬架集成系统控制的复杂性、不确定性及非线性,应用灰色预测理论、模糊控制理论和神经网络控制理论,提出电动助力转向与主动悬架集成系统动态性能灰预测模糊神经网络控制策略,研究集成系统的动态响应,设计以单片机LPC2138为内核的集成系统控制器。在仿真的基础上,进行实车道路试验。结果表明,采用灰预测模糊神经网络控制可对汽车电动助力转向与主动悬架的集成系统进行实时协调控制,汽车行驶平顺性改善的同时,缓解汽车转向时安全性与操纵稳定性之间的矛盾,提高整车综合性能。     

基于MATLAB的模糊控制系统的优化设计与仿真

介绍了利用Matlab进行模糊控制系统设计及仿真的方法，尤其为了改善模糊控制系统的性能，论述了三种主要的优化设计方法，并将模糊逻辑工具箱与Simulink仿真平台有机结合，实现了模糊控制系统的优化设计与仿真。首先利用Matlab6．5模糊逻辑工具箱图形用户界面建立模糊逻辑推理系统，然后在Simulink5．0系统仿真设计平台中，通过实例化S函数模板创建旨在优化模糊控制的S函数功能模块，并构建模糊控制系统框图模型，设置系统仿真参数，最终对系统进行动态仿真。     

基于组合方法的信息技术项目决策研究

为利用组合方法评估和确定信息技术投资,构建了基于模糊集理论的项目决策模型,其中模糊集用来刻画不确定的项目信息.融合关键成功因素法的模糊网络分析框架,用于表述信息技术项目的商业价值,并加强项目目标与企业战略的对应.权衡项目成本、收益并考虑项目间的相互关联,建立了模糊0-1整数规划,利用定性可能性理论把模糊整数规划转化成一般整数规划形式,以便求解.最后,用一个案例说明了模型的用法和如何做假设分析.     

双离合器变速汽车坡道模糊修正换挡研究

基于自主开发的5速干式双离合器变速器(dual clutch transmission, DCT)及样车,得到了双离合器变速汽车坡道模糊修正换挡规律。首先,基于纵向车辆动力学模型,运用改进型最小二乘法对整车质量与道路坡度进行实时辨识,并利用BP神经网络对实时辨识结果进行映射求解;进而,运用模糊控制方法,制定双离合器变速汽车坡道模糊修正换挡规律;最后,通过离线仿真与硬件在环实验研究验证了坡道模糊修正策略的有效性。仿真结果表明,在坡道行驶时,开发的坡道模糊修正换挡规律能有效地解决传统二参数换挡规律引起的频繁换挡和意外换挡现象,减少DCT同步器的作动次数,提高整车的舒适性。     

模糊规则调整微分作用的PID控制方法

PID控制器广泛应用于工业过程控制中 ,但对于非线性、时变不确定性的系统 ,常规 PID控制器难以获得满意效果。随着模糊控制理论的不断发展 ,利用其非线性特征 ,将其与 PID控制相结合 ,能有效改善 PID控制效果。设定值权系数的模糊逻辑整定 PID控制器 (FSW)方法在固定设定值权系数的基础上 ,用模糊推理方式计算“动态”的权系数 ,取得了一定的效果 ,但是仍存在一些问题。针对阶跃响应的上升及调整时间长、第一次超调后的反向振幅较大的缺点 ,采用模糊逻辑规则调整微分作用的改进方法 ,可以弥补上述不足。对一些典型对象进行仿真 ,结果表明该方法明显优于 Z- N方法 ,固定设定值权系数 b方法和 FSW方法     

Thirty criteria based leanness assessment using fuzzy logic approach

Nowadays manufacturing organizations are moving towards lean practices to keep pace with the competition. Lean practices mainly focuses on eliminating seven deadly wastes, thereby reducing the cost. Leanness is the measure of lean manufacturing practices. This paper presents the 30 criteria based leanness assessment methodology using fuzzy logic. Fuzzy logic has been used to overcome the disadvantages with scoring method such as impreciseness and vagueness. During this research, a conceptual model for leanness assessment has been designed. Then the fuzzy leanness index which indicates the leanness level of the organization and fuzzy performance importance index which helps in identifying the obstacles for leanness has been computed. The results indicate that the model is capable of effectively assessing leanness and has practical relevance.     

多路口模糊控制及其仿真研究

提出了一种基于模糊逻辑的城市交通面控制器,并将ARIMA短时交通流量预测与模糊控制器相结合,使路口交通信号周期适应交通流量的动态需求.进行了相关仿真,结果表明,该方法优于传统定时控制.