生物电极脱氮工艺的在线模糊控制研究(二)

系统地介绍了生物电极脱氮法模糊控制器的设计及其计算机算法，其中包括输入变量模糊化处理和输出变量非模糊化处理的计算方法，模糊控制规则的建立、模糊控制的计算机算法及其程度框图等。设计的在线模糊控制器具有结构简单、可靠、稳定、可行性好，对进水硝酸态氮负荷变化的适应性强，有利于避免过量投加有机物并尽可能节省运行费用等优点。     

运用在线监控优化生物脱氮污水处理厂的运行

运用在线监控优化生物脱氮污水处理厂的运行丹麦对污水处理厂出水中氮和磷提出新标准后，导致发展了在线监控的运行管理方法。本文介绍Ｍａｒｓｅｌｉｓｂｏｒｇ污水处理厂（ＷＷＴＰ），引用氨氮及硝酸盐监测仪的结果和在线监控法的应用。１概况对于传统活性污泥法污水处...     

自适应模糊控制技术在集中空调系统中的应用

将自适应模糊控制技术引入到集中空调PID控制系统中,以提高系统的控制精度、稳定性和其他性能。引入温湿度参考模型,构造了模糊自适应机构,实现了在线修改模糊控制系统规则库。采用三角型隶属度函数、最小值推理法和加权平均法简化了模糊推理过程。给出了自适应模糊控制技术的控制规则集、知识库修正方法和控制策略,并进行了系统仿真研究和性能分析。     

透光率脉动混凝投药系统的智能控制

利用模糊逻辑推理方法，设计了基于Takagi-Sugeno模糊逻辑方式的设定值在线自修正系统，研制开发了基于规则学习算法的自学习模糊控制器，并应用于中试。试验结果表明，这种模糊逻辑系统可在水质发生变化的情况下，及时调整透光率脉动混凝投药控制系统的设定值。调节混凝剂投加量，从而保证了沉淀出水水质稳定、合格。     

变风量空调系统温度模糊PID控制

将模糊PID控制应用于变风量空调系统中,任务是将送风温度和空调房间内的温度（回风温度）控制在各自的设定目标值附近。分别设计了变风量空调系统的送风温度模糊PID控制系统和室内温度（视为回风温度）模糊PID控制系统,通过调节冷冻水阀门的开度来控制送风温度,通过调节变频风机的转速来控制室内温度。应用所设计的模糊PID控制器对送风温度和空调房间的温度（即回风温度）进行了实时在线控制,控制结果表明模糊PID控制器设计合理,控制效果良好。     

有氧情况下同时硝化/反硝化的反应动力学模式

一般的污水处理厂都是利用生物方法脱氮。通常认为，生物法脱氮是一个两阶段过程：硝化和反硝化。在硝化阶段化学自养型硝化细菌在好氧条件下将ＮＨ４＋－Ｎ转化为ＮＯ２－－Ｎ和ＮＯ３－－Ｎ；而在反硝化阶段，兼性异养细菌在缺氧条件下进行ＮＯ２－－Ｎ和ＮＯ３－－Ｎ的...     

模糊控制在膜分离制氮设备中的应用

以膜分离制氮设备控制系统为例,介绍了基于PLC控制的温度模糊控制器。经过实际运行,具有达到设定温度时间短、反应灵敏、抗干扰能力强等优点。     

生料QCS微机控制系统的升级与改造

一、前言新疆水泥厂l＃、2＃生料磨RCS微机控制系统是80年代后期由中国建材研究院和新疆水泥厂共同研制开发的;是国家“七、五”重点科技攻关项目一“中型密控制系统”中的一个子系统。该系统自1988年投入工业运行以来,较大幅度地提高了生料出磨合格率和磨机台时产量。达到了设计要求,这也是国内建材行业较早使用成份在线控制技术且较为成功的计算机控制系统。二、系统简介RCS一862型在线生料成份配料计算机控制系统（以下简称RCS－862系统）,由在线钙铁分析仪、定量给料秤利在线配料控制计算机组成。1．硬件配置在线钙铁分析仪：选…     

短程硝化-反硝化生物脱氮

短程硝化－反硝化生物脱氮法是将硝化控制在形成亚硝酸阶段,阻止亚硝酸的进一步硝化,然后直接进行反硝化。这一方法可以克服传统生物脱氮法存在的问题,其关键是在硝化阶段维持ＨＮＯ２长久稳定地积累。本文结合国内外研究,对形成ＨＮＯ２积累的条件和影响因素进行了分析,探讨了实现短程硝化的途径。     

模糊控制技术在集中空调监控系统中的应用研究

设计了模糊控制系统结构和模糊推理机,建立了模糊控制规则库和模糊逻辑控制表,进行了模糊控制输出量的解模糊。研究结果表明,集中空调温度模糊控制系统比传统的控制系统具有更好的稳定性和节能效果。     

An Integrated Fuzzy Control System for Structural Vibration

Abstract:   Recently, numerous studies of structural control systems of civil structures and infrastructure have been carried out. To develop structural control systems, it is necessary to consider their special features such as complexity, uncertainty, and size. To consider these features, fuzzy theory has been applied to structural control systems. This study proposes an integrated fuzzy active control system based on fuzzy ensemble learning. It combines several fuzzy active control systems and improves structural vibrations caused by earthquakes. The proposed method includes two fuzzy active control systems, a fuzzy ensemble system, and a gating network. In this study, two fuzzy active control systems are constructed by applying particle–swarm optimization. The fuzzy ensemble system assigns a performance grade to each fuzzy active control system according to control effects from input patterns. The gating network determines the final control force based on the weight of their performance grade. By introducing fuzzy ensemble learning, the structural response is reduced more than when the response is controlled by individual fuzzy active control systems.     

基于SIMULINK的建筑结构模糊控制仿真

本文将模糊理论应用于结构的主动控制,并将MATLAB中的模糊工具箱和SIMLINK相结合进行了仿真.采用了改进的可调整模糊控制规则,并结合一个实例探讨了隶属函数、模糊控制规则、论域以及模糊子集划分对控制效果的影响,验证了控制的有效性,并得到了几个有益的结论.     

基于MR阻尼器的空间网壳结构模糊控制

基于模糊控制原理,提出和构建运用于大型杆系空间结构的模糊控制系统和简化模糊控制器组成,包含模糊化接口、规则库、插值查询表等.运用该模糊控制器,实现对典型网壳结构的振动控制和数值仿真.对比分析采用不同结点的位移、速度作为双输入时的结构动力响应.研究表明,该简化的模糊控制器设计简便、易于操作、振动控制效果显著.     

Hybrid Control of Structures Using Fuzzy Logic

Abstract: This investigation examined the application of control algorithms based on fuzzy logic to a class of hybrid structural control systems. The investigation included both analytical and experimental verification of the fuzzy control algorithm. The objective of the hybrid system under investigation is to obtain an ideal sliding system with perfect base isolation. As the hybrid system approaches the state of ideal isolation, the effects of imperfections, signal noise, uncertainties, modeling errors, and compensation errors start to play a dominant role in the control performance. Fuzzy logic (or fuzzy set theory) provides a simple framework to capture the effects of nonlinearities and uncertainties in a real problem without an explicit model of the plant or controller.
The applicability of this approach was first investigated analytically and then verified using a benchmark experimental model consisting of a 1:4 scale sliding-base isolated system controlled at its base by a servohydraulic actuator with a digital computer to provide the control signal. The fuzzy controller used feedback from either the acceleration of the moving foundation or the force at the interface to produce control forces in a series of shaking-table tests. The results from this study show the feasibility of the implementation of fuzzy logic to highly nonlinear problems.     

自适应模糊控制在室内采光控制中的应用研究

针对室内遮阳百叶帘运行角度的控制,在大量实验和理论研究的基础上,提出将自适应模糊控制应用于室内采光控制系统中,对百叶帘进行智能控制。介绍室内采光控制系统及工作原理,基于模糊控制规则的自适应模糊控制方法及其应用。仿真结果表明在该系统中使用自适应模糊控制具有良好的控制效果。     

Fuzzy Theory for the Active Control of the Dynamic Response in Buildings

Abstract: A new fuzzy control method for the reduction of the dynamic response of structures is presented, and is compared with the instantaneous optimal control method. The control forces are determined from preformulated fuzzy rules regarding the velocity and the acceleration of the system. The triangular membership function and the mini-max-gravity method are used in the fuzzyfication and the defuzzyfication process, respectively. In these processes, no material property of the structure such as the mass matrix or the stiffness matrix are needed. This characteristic nature is definitely different from that of optimal control algorithms. Numerical examples are shown in order to compare the performances both of the proposed fuzzy control method and the optimal control method. It appeared that the fuzzy control method is quite useful as regards reliability and robustness.     

基于模糊自适应PI控制的电梯矢量控制系统仿真研究

根据模糊自适应PID控制理论,对电梯变频调速矢量控制系统中的转速PI调节器进行优化设计。并应用电动机矢量控制系统的仿真模型进行仿真分析。仿真结果表明,采用模糊自适应PI控制器的变频调速系统具有响应时间快、超调量小等优点。     

Fuzzy Control of Base-Isolation System Using Multi-Objective Genetic Algorithm

Abstract:   In this study, a friction pendulum system (FPS) and a magnetorheological (MR) damper are employed as the isolator and supplemental damping device, respectively, of a smart base-isolation system. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme that uses a nondominated multi-objective genetic algorithm (NSGA-II) is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate the effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base-isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the NSGA-II-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semiactive control algorithm.     

A Support System for Fuzzy Optimum Aseismic Structural Design of Reinforced Concrete Buildings Using Graphical Representation

Abstract: In this paper, a support system of optimum aseismic design is proposed on the basis of fuzzy set theory and a graphical representation method. In optimum aseismic design of buildings, it is necessary to take account of subjective evaluation of users. In this system, a hierarchical model is employed to idealize and model the decision process of optimum aseismic design. By applying fuzzy set theory, this system can take account of subjective evaluation of users. The system is a prototype of an expert system for optimum aseismic design, and its knowledge is compiled interactively as numerical values by the fuzzy confluence rule and membership functions in fuzzy set theory in accordance with the hierarchical model given by users. Knowledge, which is necessary to perform the inference on optimum aseismic design, is acquired interactively. Optimization is performed by fuzzy multiobjective maximizing decision, and the maximum evaluation values of the top attribute can be found. Furthermore, distributions of the grade of membership value in maximizing the decision process are graphically represented, so the user can understand this process easily and intuitively. A case study is carried out for a reinforced concrete typical high school building in Kobe City.