模糊神经网络及其在系统建模与控制中的应用

模糊神经网络是模糊系统和神经网络的有机结合 ,它吸取了两者的优点。给出了两个具体的模糊神经网络结构以及相应的学习算法 ;介绍了利用模糊神经网络建立 T- S模糊模型的方法 ;讨论了基于 T- S模糊模型的控制系统分析和设计。     

输油管道系统的模糊可靠度研究

采用模糊状态、模糊状态转移以及模糊事件描述了机械系统状态的模糊动态过程。在模糊测度的基础上 ,建立了模糊状态下的系统可靠度计算理论 ,并用该理论研究了输油管道系统的可靠度。该理论对实现我国油气管道系统由经验管理到科学管理具有指导作用     

基于Matlab的模糊PID控制系统的设计与仿真

本文主要讨论了模糊控制及PID控制,将两种控制方法相结合,给出一个二阶惯性时滞模型,利用模糊集合论、模糊规则表及模糊逻辑推理等设计模糊控制器,应用Matlab实现了对模糊PID控制系统的仿真,具有一定的工程意义.     

模糊控制技术及其在化工中的应用

介绍了模糊控制技术的发展历程和特点，讨论了模糊控制技术的缺点和研究热点，概述了模糊控制技术在化工中的应用，提出了模糊控制技术的发展方向。     

基于聚类算法的模糊神经网络MCP预测方法研究

本文提出采用聚类算法的模糊神经网络来预测MCP。该预测模型结构简单,是数据驱动的模型,通过对输入输出数据对的模糊C均值聚类确定模糊规则的数目,解决了全连接模糊神经网络模糊规则数目难以确定以及网络复杂所带来的训练时间长的问题。     

模糊系统理论的工业应用──(Ⅱ)模糊控制系统的结构和具体实施

本文是《模糊系统理论的工业应用》专题系列之二，介绍模糊控制器和模糊控制系统的结构和组成部分，并以一个工业反应釜的温度控制为实例，详细介绍了模糊控制器的具体实施。     

连续搅拌反应釜的自适应模糊动态面控制装置及控制方法

本发明公开一种连续搅拌反应釜的自适应模糊动态面控制装置及控制方法,所述连续搅拌反应釜的自适应模糊动态面控制装置包括传感器系统、A/D转换器、计算机、滤波器、自适应模糊动态面控制器、D/A转换器、信号放大器和执行器,自适应模糊动态面控制器包括模糊逼近器、     

基于神经网络的热风炉的模糊控制

针对热风炉燃烧控制的特点,将模糊控制技术与神经网络技术相结合,提出了一种基于模糊神经网络的热风炉燃烧控制方法。该方法充分考虑了系统非线性、难以建模和具有强耦合性的特点,应用模糊神经网络对模糊规则进行快速提取,通过模糊学习,解决了模糊控制应用中规则难以获取的问题。     

模糊神经网络及其在医学诊断中的应用

神经网络和模糊技术是最近研究的热点,但是二者的缺点也十分突出。将神经网络和模糊技术融合在一起构成的模糊神经网络,在一定程度上弥补了神经网络在处理模糊数据方面的不足和纯模糊逻辑系统在学习方面的缺陷,使二者更大程度的发挥各自的特点。将模糊神经网络应用在医学诊断中,可以提高诊断的客观性和准确性,改进辅助医学诊断技术。     

基于模糊逻辑推理的精馏分离序列优化综合

模糊逻辑推理能够反映自然语言要素信息传递特性. 通过抽象有效重组参数提炼if-then模糊逻辑推理规则、根据精馏分离序列综合问题数字特征创建Sugeno模糊逻辑推理模型,系统化地提出了基于模糊逻辑推理的精馏分离序列优化综合方法.     

基于虚拟仪器中空吹塑机壁厚控制系统的开发

设计并开发了集工控机、虚拟仪器、比例伺服阀和传感器为一体的中空吹塑机壁厚控制系统.利用工控机功能强大、可靠性高的特点,结合虚拟仪器人机界面友好、编程灵活等优点,以及带位置反馈的比例伺服阀高频响、高精度的特点,采用LabVIEW中的模糊控制工具包设计模糊PID控制器,实现了高性能的型坯壁厚控制.试验表明,该系统不仅精度高、抗干扰能力强,且加工出的产品壁厚均匀,操作灵活,生产效率高.     

Adaptive type-2 fuzzy logic control of a bioreactor

Two adaptive type-2 fuzzy logic controllers with minimum number of rules are developed and compared by simulation for control of a bioreactor in which aerobic alcoholic fermentation for the growth of Saccharomyces cerevisiae takes place. The bioreactor model is characterized by nonlinearity and parameter uncertainty. The first adaptive fuzzy controller is a type-2 fuzzy-neuro-predictive controller (T2FNPC) that combines the capability of type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the nonlinear system. The second adaptive fuzzy controller is instead a self-tuning type-2 PI controller, where the output scaling factor is adjusted online by fuzzy rules according to the current trend of the controlled process. The performance of a type-2 fuzzy logic controller with 49 rules is used as reference.     

基于模糊自整定PID燃气锅炉仿真研究

针对燃气热水锅炉具有非线性、大惯性及多变量等特点,借助经验公式分析并用MATLAB系统辨识工具箱完成了系统数学模型的辨识,确定了燃气锅炉温度控制系统的模型结构可等效为一阶惯性加滞后环节,在此基础上确立了基于MATLAB的系统SIMULINK仿真框图,设计了模糊自整定PID控制器.通过模糊自整定PID与常规PID算法的仿真对比分析,得出模糊自整定PID不仅在调节时间、超调量等动态性能上的控制效果明显优于常规PID控制效果,而且增强了系统的鲁棒性和适应性,具有良好的动、静态性能.     

Control of a nonlinear continuous bioreactor with bifurcation by a type-2 fuzzy logic controller

The object of this paper is the application of a type-2 fuzzy logic controller to a nonlinear system that presents bifurcations. A bifurcation can cause instability in the system or can create new working conditions which, although stable, are unacceptable. The only practical solution for an efficient control is the use of high performance controllers that take into account the uncertainties of the process. A type-2 fuzzy logic controller is tested by simulation on a nonlinear bioreactor system that is characterized by a transcritical bifurcation. Simulation results show the validity of the proposed controllers in preventing the system from reaching bifurcation and instable or undesirable stable conditions.     

典型大时变时滞系统神经网络模糊PID控制及应用

针对典型大时变时滞系统,设计了一种基于神经网络的模糊PID控制器.该控制器综合模糊逻辑、神经网络与PID调节的各自优点,既具有模糊控制简单和有效的非线性控制作用,又具有神经网络的学习和适应能力,同时还具备PID控制的广泛适应性.该控制器能实现系统参数大范围失配情况下的闭环鲁棒稳定,并使闭环系统达到设定值无静差跟踪及满意的动态性能.     

S7-300PLC在滴灌机温度控制系统中的应用

本文论述了西门子S7—300可编程控制器在滴灌带挤出机温度控制系统中的应用,控制回路采用单参数模糊PID（比例、积分、微分）脉宽调制法。控制系统把单参数模糊PID控制和可变程序逻辑控制器的逻辑判断指令结合起来,使PID控制更为灵活,能较好地满足生产过程的要求。详细描述了该系统的工作原理和PLC的硬件组成、软件编制。     

基于模糊理论的塑料挤出机温度控制系统

提出了一种分段引入积分环节的模糊控制方法，详细介绍了模糊控制器的工作原理、模糊控制规则的确定和量表及温度控制系统的实现方法。生产实践表明，该方法能有效克服普通PID控制器和简单的模糊控制器在塑料挤出机温度控制上的缺点，具有更优良的性能。     

Fuzzy Control Of A Fluidized Bed Dryer

Fluidized bed dryers are utilised in almost every area of drying applications and therefore improved control strategies are always of great interest. The nonlinear character of the process, exhibited in the mathematical model and the open loop analysis, implies that a fuzzy logic controller is appropriate because, in contrast with conventional control schemes, fuzzy control inherently compensates for-process nonlinearities and exhibits more robust behaviour. In this study, a fuzzy logic controller is proposed; its design is based on a heuristic approach and its performance is compared against a conventional PI controller for a variety of responses. It is shown that the fuzzy controller exhibits a remarkable dynamic behaviour, equivalent if not better than the PI controller, for a wide range of disturbances. In addition, the proposed fuzzy controller seems to be less sensitive to the nonlinearities of the process, achieves energy savings and enables MIMO control.     

Control of injection velocity using a fuzzy logic rule-based controller for thermoplastics injection molding

Injection velocity to a large degree determines the melt injection rate during the injection phase, and it has critical impact on the molded part quality, such as shrinkage, warpage, and impact strength. An injection molding machine operates with different injection velocity profiles, barrel temperatures, molds, and materials. These strongly different molding conditions cause the injection velocity dynamics to very significantly and to make the control performance of the injection velocity poor with a typical PID controller. A real-time, closed-loop feedback and feedforward control system based on fuzzy logic has been designed, developed, and implemented to control the injection velocity. The fuzzy logic rules of the controller are optimized by analyzing phase plane characteristics. The controller output membership functions are optimized based on a 2^k factorial design technique. The experimental results reveal that the fuzzy logic-based controller works well with different molds, materials, barrel temperatures, and injection velocity profiles, indicating that the fuzzy logic controller has superior performance over the conventional PID controller in response speed, set-point tracking ability, noise rejection, and robustness.     

I.D.S'90, PRAGUE,CZECHOSLOVAKIA

ABSTRACT

Fluidized bed dryers are utilised in almost every area of drying applications and therefore improved control strategies are always of great interest. The nonlinear character of the process, exhibited in the mathematical model and the open loop analysis, implies that a fuzzy logic controller is appropriate because, in contrast with conventional control schemes, fuzzy control inherently compensates for-process nonlinearities and exhibits more robust behaviour. In this study, a fuzzy logic controller is proposed; its design is based on a heuristic approach and its performance is compared against a conventional PI controller for a variety of responses. It is shown that the fuzzy controller exhibits a remarkable dynamic behaviour, equivalent if not better than the PI controller, for a wide range of disturbances. In addition, the proposed fuzzy controller seems to be less sensitive to the nonlinearities of the process, achieves energy savings and enables MIMO control.