Optimal control of an unreliable machine using fuzzy-logic control: from design to implementation

In this paper, the development, implementation and validation of fuzzy logic to control an unreliable machine in manufacturing systems are presented. The fuzzy-logic controller developed in this context is based on the optimal control policy using hedging-point methodology. The fuzzy-logic controller has two-subsets of fuzzy-logic controls. The first provides a decision whether the system should produce part at make-to-stock or at make-to-order mode. The decision provided by the first fuzzy-logic control is then used by the second fuzzy-logic control to specify at what production rate the part should be produced. Simulation and implementation have been performed by controlling an unreliable machine using the developed fuzzy-logic controller. Then, the simulation results are compared with the simulation results given by the optimal control policy (hedging-point methodology). The results show that the performance of the developed fuzzy logic outperforms and is more precise than the hedging-point method under certain conditions.     

The simple and multiple job assignment problems

This paper addresses two real-life assignment problems. In both cases, the number of employees to whom tasks should be assigned is significantly greater than the number of tasks. In the simple job assignment problem, at most one task (job) should be assigned to each employee; this constraint is relaxed in the multiple job assignment problem. In both cases, the goal is to minimize the time the last task is completed: these problems are known as Bottleneck Assignment Problems (BAPs for short). We show that the simple job assignment problem can be solved optimally using an iterative approach based on dichotomy. At each iteration, a linear programming problem is solved: in this case the solution is integer. We propose a fast heuristic to solve the multiple job assignment problem, as well as a branchand-bound approach which leads to an optimal solution. Numerical examples are presented. They show that the heuristic is satisfactory for the application at hand.     

Preventive maintenance and the interval availability distribution of an unreliable production system

Traditionally, the optimal preventive maintenance interval for an unreliable production system has been determined by maximizing its limiting availability. Nowadays, it is widely recognized that this performance measure does not always provide relevant information for practical purposes. This is particularly true for order-driven manufacturing systems, in which due date performance has become a more important, and even a competitive factor. Under these circumstances, the so-called interval availability distribution is often seen as a more appropriate performance measure. Surprisingly enough, the relation between preventive maintenance and interval availability has received little attention in the existing literature. In this article, a series of mathematical models and optimization techniques is presented, with which the optimal preventive maintenance interval can be determined from an interval availability point of view, rather than from a limiting availability perspective. Computational results for a class of representative test problems indicate that significant improvements of up to 30% in the guaranteed interval availability can be obtained, by increasing preventive maintenance frequencies somewhere between 10 and 70%.     

高性能模糊控制裹包机的感应电动机驱动系统的设计与实现

针对接缝式裹包机的交流调速系统控制精度较差的问题,提出了具有模糊控制器的有限周期控制的感应电动机驱动.由于转矩和磁通是由有限周期控制技术调节,能达到极快转矩响应.将模糊控制器应用于速度控制反馈环节中,使该驱动系统具有高自适应能力,且对参数和工作条件改变是非常的不灵敏.     

采用遗传算法直接获取模糊控制器的查询表

在实际应用中,模糊控制器常常被转化为一个查询表,以减小实时运行中的计算量。这样的查询表仍然能够保留原模糊控制器的性能特征,但另一方面这个查询表是如何获得的对控制器来说并不是本质的,控制器的性能只取决于查询表本身。这样,在模糊控制器的结构下采用其他方法直接生成这种查询表,或许能够比采用模糊逻辑的方法更为有效。本文给出了采用遗传算法直接搜索查询表的方法,以获取性能优良的控制器,给出了查询表式下二队控制     

Improved Electric Arc Furnace Operation Via Implementation of a Geno-Fuzzy Control System

The U.S. steel industry is growingly increasingly interested in the process of slag foaming in their electric arc furnace plants. Although slag foaming has been shown to improve plant efficiency, this highly dynamic process can be very difficult to consistently control. This article describes a computer control system developed to effectively manipulate the slag foaming process, and the implementation of the controller in an electric arc furnace plant. The control system is a model-following controller based on fuzzy logic. It uses a neural network to simulate the slag foaming process. Furthermore, the control system uses an evolutionary algorithm to effectively tune its fuzzy rule base in response to the dynamic behavior of the slag foaming process. Results are presented, which demonstrate the effectiveness of the control system in this process characterized by relatively slow process dynamics.     

基于遗传算法的模糊神经控制及其应用

将遗传算法和模糊神经网络相结合，提出了一类智能控制方案，仿真系统和实际温控表明，这类智能控制器可改善具有时变、非线性及大纯滞后系统的控制品质，其性能优于一般模糊控制。     

DSP全模糊控制包装机的凸轮定位差动器的交流伺服系统

根据裹包机的伺服系统控制精度较差的问题,提出由DSP实现的四个模糊控制器组成的全数字、高动态性能的凸轮定位差动器的交流伺服系统,采用空间矢量PWM调制器,仿真和实验结果是完全一致的.该系统的主要优点是研究时间缩短,且不需明确的数学模型.     

蜂窝纸板切纸机的模糊神经网络智能化控制

提出并实现了一种基于模糊技术和神经网络集成的仿人智能控制模型,利用该智能控制模型对蜂窝纸板切纸机进行控制,可以实现对纸板的按任意要求的切割。仿真实验证明了该模型的可靠性和快速性。     

Tolerancing for manufacturing: A three-dimensional model

This paper proposes a three-dimensional (3D) model on manufacturing tolerancing for mechanical parts. The work presented relies on research conducted at the LURPA on the computation of 3D tolerance chains for mechanisms. Starting from these works, the authors propose a formalization of the problem within the more specific context of manufacturing tolerances. Models of the workpiece, the set-ups and the machining operations are provided. The main originality is to model the machining set-up as a mechanism. The concept of the small displacements torsor (SDT) is used to model the process planning. It opens up the way for the 3D integration product/process because of the similarities between the concepts used in both points of view. The first part recalls the principle of the modelling of surface variations with SDT as well as its application to the modelling of mechanisms. The second part introduces the use of the concept in the case of manufacturing tolerancing. A third part shows the modelling of the problem with the help of an example. At last, a detailed computer implementation is described.     

Multilevel intelligent scheduling and control system for an automated flow shop manufacturing environment

Current manufacturing scheduling and control systems are incapable of coping with complex system dynamics inherent in real-world situations and, hence, human intervention is required to maintain real-time adaptation and optimization. A unique feature of biological intelligent systems is that they build and improve over their communication, decision-making and control structures in real time autonomously. A challenge is now emerging in the design of manufacturing systems where on-line adaptation and optimization become increasingly important. This paper reports on the development of a new integrated intelligent scheduling and control system for an automated manufacturing environment using a multilevel approach. At the first level, a conventional scheduling and control system is considered, then at the second level, a new fuzzy logic mechanism is developed to enable the conventional system to improve and perceive the changes of system parameters adaptively. A new perturbation mechanism is embedded in the third level to implement on-line optimization for coping with the more complex structural changes of system dynamics. The final level is composed of artificial neural networks that can learn from experiences provided by the perturbation mechanism. The approach is designed to improve system intelligence gradually to cope with various forms of systems dynamics. A fully automated flow shop manufacturing system is taken to demonstrate this approach.     

An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart

This paper proposes a model for the economic design of a variable-parameter (Vp) Shewhart control chart used to monitor the mean in a process, where, apart from quality shifts, failures may also occur. Quality shifts result in poorer quality outcome, higher operational cost and higher failure rate. Thus, removal of such quality shifts, besides improving the quality of the outcome and reducing the quality cost, is also a preventive maintenance (PM) action since it reduces the probability of a failure and improves the equipment reliability. The proposed model allows the determination of the scheme parameters that minimize the total expected quality and maintenance cost of the procedure. The monitoring mechanism of the process employs an adaptive Vp-Shewhart control chart. To evaluate the effectiveness of the proposed model, its optimal expected cost is compared against the optimum cost of a fixed-parameter (Fp) chart.     

Fuzzy logic control of vehicle suspensions with dry friction nonlinearity

We design and investigate the performance of fuzzy logic-controlled (FLC) active suspensions on a nonlinear vehicle model with four degrees of freedom, without causing any degeneration in suspension working limits. Force actuators were mounted parallel to the suspensions. In this new approach, linear combinations of the vertical velocities of the suspension ends and accelerations of the points of connection of the suspension to the body have been used as input variables. The study clearly demonstrates the effectiveness of the fuzzy logic controller for active suspension systems. Suspension working space degeneration is the most important problem in various applications. Decreasing the amplitudes of vehicle body vibrations improves ride comfort. Body bounce and pitch motion of the vehicle are presented both in time domain when travelling over a ramp-step road profile and in frequency domain. The results are compared with those of uncontrolled systems. At the end of this study, the performance and the advantage of the suggested approach and the improvement in ride comfort are discussed.     

双模模糊滑模控制裹包机交流转矩系统

针对接缝式裹包机交流伺服系统控制精度差的问题,采用了双模模糊滑模变结构控制器,仿真结果表明该方案有效地消除了抖动问题,具有优良的动静态性能,证明了双模模糊滑模变控制方法的合理和优越。