A VLSI fuzzy expert system for real-time traffic control in ATMnetworks

Concerns a fuzzy logic-based system which has been purposely designed to achieve real-time traffic control in high-speed networks using the asynchronous transfer mode (ATM) technique. One of the most critical functions is “policing”, which has the task of ensuring that each user source complies with the traffic parameters negotiated in the call setup to avoid network congestion. This function is difficult to implement on account of certain conflicting requirements such as selectivity and responsiveness. This is confirmed by the severe limits affecting the most popular mechanisms proposed so far, based on conventional logic. The capacity to formalize approximate reasoning processes offered by fuzzy logic is exploited to derive rules of behavior for a policer starting from the know-how of an expert. We address two key issues related to the implementation of the fuzzy policer. The first focuses on the possibility of hardware implementation of the mechanism using VLSI technology; we present the design of a VLSI fuzzy processor which exhibits a level of performance of over 3 MFLIPS. The second issue concerns the suitability of applying the fuzzy policer to the policing of several classes of sources to reach high levels of cost effectiveness and scalability     

A novel structure of real-time expert control system for process industry

A new structure of on-line real-time expert control system for process industry is proposed in this paper. The overall system can be hierarchically visualized as three levels. The highest level performs the supervisory functions, such as overall system performance monitoring, possible system components failure detections and diagnoses; and commands generations regarding to the necessary controller parameter tunings or structure variations. It is in this level that the expert control system stores the knowledge and makes the decisions. The second level utilizes some sophisticated signal processing algorithms, such as adaptive filtering, system identification, state estimation, to pre-process the raw measurement data coming from the sensors. So that the procedure of decision-making and structure of the knowledge base become simpler and more concise. It is this level that makes the present structure unique in comparison with the other existing expert control systems. The lowest level consists of the conventional control hardwares which execute the control commands. A prototype system is under construction on an IBM PC-AT microprocessor using PROLOG for knowledge manipulation, decision-making and FORTRAN for numerical computations.     

Android fine-grained permission control system with real-time expert recommendations

In current Android architecture design, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to prevent unnecessary privacy breach. However, inexperienced users may not be able to decide correctly. To assist inexperienced users to make a right permission granting decisions, we propose RecDroid. RecDroid is a crowdsourcing recommendation framework that facilitates a user-help-user environment regarding smartphone permission control. In this framework, the responses from expert users are aggregated and recommended to other users. We implement our prototype on Android platform and evaluated the system through simulation and real user study.     

A predictable real-time expert system for multi-sensor fusion

Predictability of response times is crucial for real-time expert systems. In this paper, we discuss the importance of the determinism of response times and analyse the conditions under which each maximum response time will be predictable. We present also the application of the concepts described to multi-sensor fusion.     

Problems with expert systems in real-time control

There is increasing use of knowledge-based or expert systems in the process and manufacturing industries, with currently in excess of 2000 installations. The advantage offered by such systems is their ability to deal with complex and possibly incorrect or incomplete data. A new generation of expert-system tools, designed specifically for real-time control applications, has been developed. This paper examines the requirements of an expert system for real-time control, and shows how current approaches attempt to meet them. It is argued that none of the currently available tools fully satisfy the needs of a real-time expert control system, particularly in terms of reliability and guaranteed real-time response.     

基于神经网络的实时专家控制系统及其PTA工业应用

以精对苯二甲酸结晶过程为研究对象。提出一种基于神经网络模型的实时专家控制系统．该方法利用神经网络建模技术获取对象的机理知识,通过对影响模型特性的多个变量进行分析,自动得到常规专家控制系统难于获取的定性、定量知识,并按分级递阶的启发式搜索机制,实现了对工业过程对象的实时控制．实际应用表明：该方法不但克服了以往专家系统知识获取的瓶颈,而且有效实现了人机对话的功能,便于现场操作和更改专家知识库,为化工过程的多变量控制提供了新的思路．     

A fuzzy expert system approach for real-time monitoring of endemic diseases

In this paper, an architecture of LEPDIAG—a knowledge based system for on-line diagnosis and for monitoring prognosis of leprosy—is presented. The important features of LEPDIAG that have been detailed are a multiple expert environment, a homeostatic expert containing the model of immune reaction, a performance evaluator that can compare the observed signs and symptoms with those predicted by homeostatic expert, and a prognostic expert which optimizes the management schedule for the patients. The entire system is built around a fuzzy expert system building tool FRUIT to deal with the imprecise knowledge.     

A hierarchical expert system for computer process control

This paper reports on the design and implementation of an expert system for computer process control (HESCPC). The complexity of the expertise necessary for computer process control applications requires that the expert system architecture be structured into a hierarchy of classes of specialized experts. The architecture of HESCPC integrates four classes of expert systems: operator/manager companion expert class, control system algorithm design expert class, hardware expert class, and software expert class. The paper is concerned with the design and implementation of the general system architecture, an operator adviser expert for a nuclear power plant and a control system designer expert using a state space feedback approach. Although the design and implementation aspects of all experts are discussed, the emphasis is on the latter.

At this stage of the HESCPC development, the declarative knowledge represented by 423 metarules and 1261 rules is distributed on a hierarchical structure among 20 experts on different levels of the hierarchy which are able to communicate among themselves to solve difficult control problems.

Examples of control system design sessions of linear mono and multivariable systems using feedback state space approach are given. A run time of an operator-adviser data-driven expert system for a nuclear plant is also presented.     

用于控制系统实时监控的专家系统设计

在某型装备的大型指挥控制系统中,电路节点错综复杂,由其中某些节点的短路或断路可能导致很多故障.在实际的操作中,由于需要进行实时控制,必须能够及时发现并解决问题.本文提出了一种基于故障树分析和统计概率的模块化专家系统,作为此大型指挥控制系统电路的故障实时监测之用.     

A distributed expert control system for a hydrometallurgical zinc process

A distributed expert control system (DECSHZ) has been built for a hydrometallurgical zinc process, whose basic steps are leaching, purification and electrolysis. It consists of a central computer management system and three local expert control systems, one for each of the basic steps. This paper deals with the design and application of DECSHZ, especially its distributed architecture and main functions; expert control strategies based on rule models and a combination of rule models and steady-state mathematical models; system implementation; and the results of actual runs. DECSHZ has been found to provide not only a very pure product, but also significant economic benefits.     

An expert system for manufacturing cell control

An expert control system was designed to control an unmanned manufacturing cell in order to meet the operational requirements of a cellular Manufacturing System (CMS). In this paper, a knowledge-based three-layer control concept was used to build the cell control system. This cell control system is built to include workers' experience and problem handling ability. The cell control algorithms and heuristics are based on the pull system control principle. A Petri net is used to generate the cell control algorithm. The structure of the control system and the application of the Petri net method will be demonstrated.     

An expert system approach to quality control

This paper describes the basic actions proposed for quality inspection. These actions involve structuring a Decision Supporting Expert System (DSES) to help with those decisions related to the preliminary activities for inspection development—most of them relating to determining of the need or convenience of carrying out the inspection itself. Once the opportunity to carry it out is defined, the expert system helps the user to select the type of inspection to adopt from amongst: (1) automatic or sensorial inspection; (2) inspection by samples or complete; (3) acceptance or rectifying and, in the most relevant module, (4) inspection by attributes or by variables. The complementary documentation of the DSES contains the directions to operate it, the rules and qualifiers that make up the system, as well as the results achieved through its experimental implementation.     

A castability expert system

The castability analysis of a part, its cost estimation and preparation of competitive quotations typically requires years of experience, is time consuming and is dependent on the expert personnel available. Considerable amount of personnel time is also involved in preparing these quotations. An expert system is ideally suited for this application as it can automate the castability analysis and the quotation preparation process. This will not only substantially improve productivity and consistency, but also the accuracy of the process. This paper describes the development and implementation of an expert system for a typical medium sized company, which receives approximately thousand requests for quotations every year. A Castability Expert System apart from reducing time and increasing accuracy, will enable people with little experience to analyze the part, estimate cost and prepare quotations without the assistance of an expert, whose time can be better utilized in other areas.     

A combinatorial decision-generating method for expert systems in complex system control

An expert control model for complex systems is proposed. The expert system generates decisions taking into account the consequences of their implementation.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 81–87, September–October, 1992.     

An expert system for real-time fault diagnosis of complex chemical processes

This paper presents the development and implementation of an expert system for real-time fault diagnosis of chemical processes. The expert system is applied as a real-time computer aided decision support system, providing operation suggestions to help field operators when abnormal situations occur. The knowledge base structure, representation of knowledge, and access to expertise are technically considered. Industrial applications to the fluid catalystic cracking process in refinery indicate that the expert system diagnoses abnormal events efficiently and promptly.     

Fuzzy expert system for real-time process condition monitoring and incident prevention

A new fuzzy expert system for real-time process condition monitoring and incident prevention is developed. Its reasoning strategy is based on dynamic membership functions of fuzzy systems. With a multimedia user interface, the fuzzy expert system can codify the expertise knowledge to handle incidents, perform process condition monitoring, and provide operation support. The prototype of this system has been successfully used in a chemical pulp mill for process condition monitoring and incident prevention.     

Developing an expert system to assist in control system design

This paper addresses the problem of how to develop an expert system that is able to design or to assist in the design of a control system. The discussion includes how to structure the expert system, how to choose the relationship between the symbolic and numerical processor and how to divide the work among the expert system, the computer aided control systems analysis package and the design engineer. A prototype intelligent design associated is presented and an example of a compensator design is given.     

结晶器液位专家系统控制研究

针对传统的结晶器液位控制系统方案存在缺点,根据对象机理,比较了塞棒比例积分（PI）控制和拉速PI控制和对结晶器液位控制效果,分析了塞棒PI控制液位存在的问题,设计了基于径向基函数神经网络（RBFNN）的塞棒控制器和拉速补偿器。使用规则模型,研究了基于专家系统的塞棒和拉速控制液位的协调控制系统,解决了液位控制器切换存在的干扰。系统在MATLAB上进行了仿真,并在实际中进行了测试。实际测试结果表明该系统的液位控制精度、稳定性和动态响应优于传统的单回路控制方案。     

QEX: An in-process quality control expert system

True computer-integrated manufacturing requires that many links between factory processes become more automated, more computerized, and more intelligent. Many links between processes, however, are based on human judgement, experience, and intuition. These are naturally difficult tasks to automate, but the advent of artificial intelligence, and specifically expert system programming, has made such links possible. This paper presents a research effort toward one of these links, that of quality control judgements of ongoing processes. The use of expert system programming, combined with in-process metrology and system integration, allows the factory to be more fully automated and computer-integrated, resulting in higher precess precision and lower production errors. This paper will discuss how the expert system approach is used to integrate the quality judgement process into the production process, and bring the factory one step further toward total CIM.