MODELING AND CONTROL OF INTERNAL COMBUSTION ENGINES USING INTELLIGENT TECHNIQUES

This article will compare two different fuzzy-derived techniques for controlling small internal combustion engine and modeling fuel spray penetration in the cylinder of a diesel internal combustion engine. The first case study is implemented using conventional fuzzy-based paradigm, where human expertise and operator knowledge were used to select the parameters for the system. The second case study used an adaptive neuro-fuzzy inference system (ANFIS), where automatic adjustment of the system parameters is affected by a neural networks based on prior knowledge. The ANFIS model was shown to achieve an improved accuracy compared to a pure fuzzy model, based on conveniently selected parameters. Future work is concentrating on the establishment of an improved neuro-fuzzy paradigm for adaptive, fast and accurate control of small internal combustion engines.     

MODELING AND SIMULATION FOR INTELLIGENT CONTROL OF EXPANSION VALVE IN VAPOUR COMPRESSION REFRIGERATION SYSTEM

Conventional control techniques are not able to accomplish the stable cooling in VCRS (vapour compression refrigeration system) of air conditioning system. This article describes the fuzzy modeling and simulation for intelligent control to regulate the opening area of expansion valve for better and stable refrigerant flow even in the presence of operating condition change. Fuzzy logic control of expansion valve can make a quick response to the abrupt changes of operating parameters in VCRS. The expansion valve opening trend depending upon differential pressure across it (delP) and refrigerant mass flow rate is analyzed with fuzzy modeling using ANFIS. Differential pressures in the range of 3–7 bar are sustained across the valve. Flow rates up to 0.15 kg/sec for the refrigerant R-134a have been demonstrated. The performance of the model is evaluated by comparing the predicted results with the standard mathematical model.     

智能控制与常规控制

智能控制是在常规控制理论与技术基础上的进一步发展与提高，目的是在非结构化、不确定性与控制对象有强相互作用的环境中实现过程任务（追求目标）的闭环自动控制。虽然传统人工智能方法应用于实际控制问题有很大困难，但是把对复杂环境建模的严格数学方法研究同人工智能中新兴学派思想的研究紧密结合起来，有可能导致新的智能控制体系结构的产生和发展。这种研究将会在＂自上而下＂和＂自下而上＂两个方向的交汇处取得重大突破。     

智能建模方法中的数据预处理

本文对智能系统建模中的数据预处理问题进行了研究，指明了这一工作的重要性．结合一个 系统建模的例子阐明了在智能建模方法中进行辅助变量初选、数据采集、数据处理与校正、 输入数据集降维等各种数据预处理工作的思路与方法，为系统模型的准确建立提供了保证．     

工作流管理系统中协同建模环境的研究

工作流建模是工作流技术能否在企业中成功应用的一项关键技术。传统工作流管理系统中的建模工具只支持单用户建模,不利于对持续变化、不可预测的市场需求做出迅速而准确的反应。提出了一个工作流管理系统中协同建模环境的概念框架,并对该框架中的相关内容：协同建模语言、访问控制、建模相关信息的感知以及模型定义冲突的管理作了讨论,最后展望了下一步的研究内容。     

基于范例推理的交通事故智能处理系统

介绍了一个基于范例推理的交通事故智能处理系统。首先给出了基于CBR的交通事故智能处理系统的总体框架。之后,对该系统中的核心部分：范例搜索、基于范例推理的综合推理模型、人机智能系统分别进行了讨论。     

INTELLIGENT SYNTAX-DIRECTED EDITOR THAT MODELS USER PROFICIENCY

Current interactive software systems try to offer many features and a user-friendly interface to aid the user. However, where one system may suit one user, another user may find it difficult to use, because each user is different. User modeling techniques have been applied to make a system suitable for different users. This paper surveys research works for developing interactive systems that use user modeling techniques. After presenting the systems and techniques, we introduce a system called the Intelligent Syntax-Directed Editor (ISE) as an example to show how this approach can benefit the user as an intelligent tool. The ISE assists the user in (1) using the editor more efficiently through ISE's active suggestions and on-line help and (2) program development through the syntax-directed editor. In applying user modeling techniques, ISE builds a profile/model of the user and, based on this model, ISE offers a suitable amount of help and advice depending on the proficiency of the user toward the system. The ISE is implemented on a VAX/780 computer to demonstrate its ability to volunteer advice     

TOPS: AN INTELLIGENT ASSOCIATE FOR TURNING OPERATION PLANNING

This article describes the development of a new modeling environment that supports the building of intelligent associates for turning operation planning. By intelligent associates, we mean a computer-based system that allows a process planner to assert a greater degree of control during a consultation than do traditional expert systems. Intelligent associates are able to assist process planners in a colleague-like manner while solving domain tasks. They relieve routine operations while supporting creative problem-solving. Multiple levels of human experience are supported, advising and constraining inexperienced planners while providing a flexible environment for experienced planners working on new planning strategies. Several Al-based techniques have been employed in the development of this new modeling environment. The utility of this environment is demonstrated by developing a turning operation planning intelligent associate (TOPS). TOPS assists a process planner by computing interactions and checking for consistency among the various attributes of a lathe machine-operation planning problem and searching databases for machines, tool holders, and inserts.     

一类专家智能控制器的设计与实现

本文提出光导纤维拉丝过程张力控制的实时专家智能控制器。该控制器在 IBM—PC 微机系统上实现。张力闭环控制系统的良好运行结果表明,我们设计的专家智能控制器完全满足张力控制系统的要求。     

USING LEAST SQUARE SVM FOR NONLINEAR SYSTEMS MODELING AND CONTROL

Support vector machine is a learning technique based on the structural risk minimization principle, and it is also a class of regression method with good generalization ability. The paper firstly introduces the mathematical model of regression least squares support vector machine (LSSVM), and designs incremental learning algorithms by the calculation formula of block matrix, then uses LSSVM to model nonlinear system, based on which to control nonlinear systems by model predictive method. Simulation experiments indicate that the proposed method provides satisfactory performance, and it achieves superior modeling performance to the conventional method based on neural networks, moreover it achieves well control performance.     

智能Agent技术在WBT中的应用

智能Agent技术近年来有了很大的发展，本文提出一种利用智能Agent技术来构建Web Based Training系统的框架模型，实现在线培训系统的智能性、交互性和协同性，克服现阶段在线培训系统的一些不足之处。     

基于系统辨识的燃料电池系统建模和自适应模糊控制

熔融碳酸盐燃料电池（MCFC）发电运行时，电堆的工作温度必须控制在一定的范 围内，否则将导致系统发电效率的降低或危及电堆寿命．因此，实现对MCFC运行温度的在线 控制势在必行．但由于MCFC系统的复杂性，已有模型均为复杂的非线性微分方程组描述的解 析模型，难以满足在线计算的实时控制的要求．因此，本文首先利用神经网络辨识技术基于 实验的输入（气体流量）输出（温度）数据建立起MCFC电堆的神经网络模型；然后，基于这 一电堆模型，设计了一个MCFC电堆工作温度的在线改进型自适应模糊控制器．该控制器对传 统的模糊控制方法存在的缺陷进行了改进，它一方面采用BP算法对模糊系统的参数进行修正 ，另一方面又通过聚类算法对模糊系统的结构进行自适应调整．最后，用神经网络辨识模型 代替实际的MCFC电堆进行了控制仿真，仿真结果证明对MCFC辨识电堆建模的有效性，以及所 设计的模糊控制器的性能优越性．     

智能型多方案综合评价支持系统的设计与实现

本文提出了一个智能型多方案综合评价支持系统的基本结构框架；描述了多目标多层次模糊综合评价的数学模型；讨论了ＩＡＣＥＳＳ的主要实现方法与技术。整个ＩＡＣＥＳＳ已在ＩＢＭ ＰＣ机上实现。     

AN INTELLIGENT TUNING CONTROL TECHNIQUE

This paper argues that existing adaptive control algorithms are limited in many practical applications because they lack the inclusion of human intelligence, knowledge, reasoning skills, and human-machine interaction. To solve these problems, an Intelligent Tuning Control (ITC) technique is presented. The TTC technique combines expert system technology and adaptive control techniques and integrates numeric computation with symbolic reasoning. Since most physical systems have uncertainties to some extent, an inexact reasoning method is proposed in the knowledge-based component. The TTC system is implemented using a Lisp-based expert system shell on an IBM PC. The utility of the TTC technique has been positively confirmed by simulation results.     

AI AND INTELLIGENT INDUSTRIAL APPLICATIONS: THE ROUGH SET PERSPECTIVE

Application of intelligent methods in industry become a very challenging issue nowadays and will be of extreme importance in the future. Intelligent methods include fuzzy sets, neural networks, genetics algorithms, and other techniques known as soft computing. No doubt, rough set theory can also contribute essentially to this domain. In this paper, basic ideas of rough set theory are presented and some possible intelligent industrial applications outlined.     

智能控制与智能控制系统

本文首先介绍智能控制的发展和智能控制系统的结构与特点.然后,综述几种主要的智能控制系统,尤其是分级递阶智能控制系统和专家控制系统,并着重讨论它们的结构.     

工业醪塔的建模,仿真及最优化

以工业醪塔（丙酮－丁醇）为对象，阐述了如何利用ＵＮＩＦＡＣ功能团法建立精馏过程的静态数学模型，针对醪塔模型变量多，非线性严重，不易收敛等情况，提出了一种改进的Ｎｅｗｔｏｎ－Ｒａｐｈｓｏｎ法，保证了算法和收敛性和快速性，根据现场操作数据，对模型进行参数辨识和修正，结果表明模型与塔吻合良好，基于该模型建立了可用于工厂实际操作指导的仿真系统，并以节能粮为目标函数，离线优化了操作条件，为工厂提高经济效益提     

人—机智能分工算法设计与人—机接口智能值计算

本文系统地提出了一个适用于人—机合作智能系统的人—机智能任务分配定量算法．在定义机器智能和人—机接口智能的基础上，为人—机合作智能系统引入一个模拟和分析系统智能的工具，即智能任务图．通过使用智能任务图及其描述的方程，能够把人—机合作智能系统需要完成的任务分解为人承担的任务和机器承担的任务,同时能够对人—机接口性能进行分析和优化．通过实例计算，证实了该算法在人—机合作智能系统设计和分析中的有效性和重要性．     

模糊树模型及其在复杂系统辨识中的应用

基于二叉树和模糊逻辑理论,提出了一种用于复杂系统建模的模糊树模型.将线性 模型和模糊集组织在树结构上,并给出了更新线性模型系数和模糊集隶属度函数的混合算 法.与其他建模方法相比,如ANFIS,模糊树模型计算量小,精度高,尤其在高维数据建模中 更为明显.仿真结果描述了这种方法的性能.