135MW循环流化床机组过热汽温优化控制方案研究

大多数火力发电厂的过热汽温控制采用的是DCS自带的经典PID控制。这类控制系统对于滞后性较大的高阶被控对象、现场执行机构死区大和减温阀线性差等工况,其控制品质较差。如果将无辨识自适应控制器IFA、预估与大数据智能诊断等先进技术引入到锅炉过热汽温控制系统中来,优化DCS系统算法逻辑,这不仅能控制过热汽温在额定值允许范围这内,而且可以适当提高过热汽温,提高蒸汽品质。另一方面可以省去升级改造喷水减温装置即可投入自动,其经济效益是相当可观的。     

单元机组协调控制系统模糊自适应控制研究

单元机组协调控制系统的负荷控制对象存在耦合性和时变性,常规PID控制方案在负荷大范围变化时控制效果变差.为了提高协调控制系统的调节性能,采用了一种模糊自适应控制方案.基于300MW直流锅炉单元机组不同工况下采集的数据,建立了机组在210MW和270MW工况下的负荷控制对象动态数学模型,并进行了动态特性分析;基于常规PID协调控制方案,设计了一种模糊自适应PID控制器,可以自动调整控制器参数以适应工况的变化.锅炉控制器和汽轮机控制器均采用模糊自适应PID控制器.仿真结果表明,单元机组协调控制系统模糊自适应控制与常规PID控制相比,超调量降低,调节时间缩短,抗干扰能力和负荷适应能力增强.     

基于改进DE算法的PID参数整定及其应用

将PID经验整定公式和自适应算子引入到微分进化(DE)算法中,在此基础上提出了改进的微分进化(IDE)算法,即采用PID经验整定公式指导DE算法中初始种群的产生,减少了DE算法寻优的随机性,加快了收敛速度且不依赖调试人员的经验,实现完全自适应获得PID参数.对具有严重参数不确定性、多扰动及大迟延的循环流化床(CFB)锅炉汽温控制系统进行仿真研究,并将IDE算法应用到某300 MW CFB锅炉主汽温控制系统中.结果表明:IDE算法寻优速度快、计算量小,对参数优化非常有效;与遗传算法(GA)整定PID参数的效果相比,IDE算法具有较好的调节品质和较强的鲁棒性,汽温控制效果得到明显改善.     

模糊滑模自适应控制及其在电厂热工过程中的应用

通过一种新学习算法的导出,并结合模糊逻辑系统中的模糊基函数,给出了一种带有通用规则库的模糊滑模自适应控制器。这种控制器能够在线自动调整参数,能对热工过程中的大惯性大迟延对象进行有效的控制。当对象参数变化或存在较大扰动的情况下,仍能保持很好的控制品质。该方法已被用于某电厂主汽压力控制系统。仿真结果表明:该算法具有良好的控制品质和很强的鲁棒性。图4表1参7     

改进的自适应模型算法控制在过热汽温控制中的应用

针对锅炉过热汽温对象具有大惯性、大迟延、时变性等特点,提出一种基于最小均方算法的自适应模型算法控制-比例串级预测控制系统.通过最小均方自适应滤波器在线实时辨识被控对象的预测模型参数,再结合改进的自适应模型算法控制在线修正控制器参数.仿真结果表明:该控制策略实施简单、超调小,控制效果明显优于PID-P串级控制;且在降负荷实验中能有效适应对象参数时变,保证调节性能较好.     

基于灰色预测的汽温模糊免疫PID控制

火电厂汽温具有大惯性、大迟延和时变等特性,采用常规的PID串级控制方法难以取得满意的控制效果.借鉴生物免疫反馈响应过程的调节作用和模糊推理逻辑可逼近非线性函数的特性,结合灰色预测的优点,提出采用灰色预测的模糊免疫PID控制策略.火电厂汽温控制系统的仿真研究表明:该方法的控制品质良好,能适应对象参数的变化,具有较强的鲁棒性和自适应能力.     

基于插值和拟合技术的过热汽温非线性控制研究

针对过热汽温对象特征参数在负荷范围内变化较大的特点,提出一种基于插值和拟合技术的过热汽温非线性自适应控制方法,通过调节控制器参数使其随负荷自动变化来保证系统的鲁棒性。首先简单介绍了过热汽温串级控制和采用插值与拟合技术获取控制器参数的方法,然后提出一种连续变速积分不完全微分数字比例、积分、微分(PID)控制算法。基于典型工况下的PID参数和插值及拟合技术建立了过热汽温全工况下的自适应控制器,并对某超临界600 MW直流锅炉过热汽温对象进行了仿真。分析了不同插值和拟合方法下自适应PID控制的控制效果,证明了本文方法的有效性。     

火电厂主汽温控制系统的免疫PID串级控制

火电厂主汽温控制系统具有大惯性、大延迟和时变等特性,采用常规PID串级控制方法的主汽温系统难以获得满意的控制效果。生物免疫系统是一种在大量干扰和不确定性环境中都具有很强鲁棒性和自适应性的系统。借鉴生物免疫反馈响应过程的调节规律,提出将免疫PID串级控制策略应用到火电厂主汽温控制中,针对某超临界600MW锅炉高温过热器在4个典型工况点的仿真研究表明,该策略的控制效果优于常规的PID串级控制,它能适应对象参数的变化,具有较强的鲁棒性和自适应能力。图5表2参8。     

基于免疫疫苗的主汽温系统PID优化整定

为了达到主汽温系统的优化运行以提高热效率,在自适应遗传算法基础上引入基于免疫原理的免疫记忆细胞和疫苗提取、接种算子的免疫疫苗算法,进行了收敛性证明,将其用于主汽温控制系统的PID优化整定,并将获得的PID参数的控制效果与自适应免疫遗传算法(AIGA)获得的PID参数的控制效果进行了比较.结果表明:自适应免疫疫苗算法(AIVA)的收敛稳定性优于自适应免疫遗传算法,与自适应免疫遗传算法获得的PID参数的控制效果相比,自适应免疫疫苗算法所产生的PID参数的控制效果更好,且阶跃响应的调节时间较短,过渡更平稳,证明了该方法的有效性.     

模糊自适应导前微分方式的过热汽温控制系统

针对某机组锅炉主汽温被控对象动态特性迟延有惯性大、时变非线性强的特点，采用了模糊自适应导前微分双回路控制方案。实验表明，采有这种方法建立的主汽温控制系统比常规控制方案具有更好的控制品质和更强的抗干扰能力，提高了系统的鲁棒性，而且计算工作量汴，实时性能满足生产现场的要求。     

Adaptive fuzzy sliding-mode control for induction servomotor systems

An adaptive fuzzy sliding-mode control design method is proposed for induction servomotor system control. The proposed adaptive fuzzy sliding-mode control system is comprised of a fuzzy controller and a compensation controller. The fuzzy controller is the main tracking controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the fuzzy controller. A tuning methodology is derived to tune the premise and consequence parts of the fuzzy rules. The online tuning algorithm is derived in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Moreover, to relax the requirement for the uncertain bound in the compensation controller, an estimation mechanism is investigated to observe the uncertain bound, so that the chattering phenomena of the control efforts can be relaxed. To illustrate the effectiveness of the proposed design method, a comparison between a conventional fuzzy control and the proposed adaptive fuzzy sliding-mode control is made. Simulation and experimental results verify that the proposed adaptive fuzzy sliding-mode control design method can achieve favorable control performance with regard to parameter variations and external disturbances.     

内燃机整机振动模糊自适应主动控制技术研究

作者在建立发动机一汽车振动模型中，利用模糊自适应主动振动控制与机械被动隔振相结合的方法，使得模糊控制规则在控制过程中自动调整、修改和完善，从而达到了最佳的控制效果。应用MATLAB语言编程仿真表明，设计的模糊自适应控制系统的振动控制效果优于机械被动隔振和传统的主动隔振，而且对振动环境的自适应能力强，控制器响应快，超调量小，有很强的鲁棒性。     

Developing a multipurpose sun tracking system using fuzzy control

The present work demonstrates the design and simulation of time controlled step sun tracking systems that include: one axis sun tracking with the tilted aperture equal to the latitude angle, equatorial two axis sun tracking and azimuth/elevation sun tracking. The first order Sugeno fuzzy inference system is utilized for modeling and controller design. In addition, an estimation of the insolation incident on a two axis sun tracking system is determined by fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm, along with least square estimation (LSE), generates the fuzzy rules that describe the relationship between the input/output data of solar angles that change with time. The fuzzy rules are tuned by an adaptive neuro-fuzzy inference system (ANFIS). Finally, an open loop control system is designed for each of the previous types of sun tracking systems. The results are shown using simulation and virtual reality. The site of application is chosen at Amman, Jordan (32° North, 36° East), and the period of controlling and simulating each type of tracking system is the year 2003.     

Adaptive fuzzy control for wind-diesel weak power systems

This work is concerned with the development of an adaptive fuzzy logic controller for a wind-diesel system composed of a stall regulated wind turbine with an induction generator connected to an AC busbar in parallel with a diesel generator set having a synchronous generator. In this work we propose to use an adaptive network based inference system (ANFIS) in order to generate fuzzy membership functions and control rules for the controller. A feedback linearized proportional integral controller is used to provide the required expert knowledge. A controller design process is identified; it consists of generating input-output data pairs to identify the control variables range and initial fuzzy memberships, and then to tune or adapt them using an ANFIS network structure. The controller inputs are the frequency error and its integral for the governor part of the controller, and the voltage and frequency errors for the automatic voltage regulator. These are readily measurable quantities leading to a simple controller which can be easily implemented     

水轮发电机组的直接自适应模糊控制

提出了一种新颖的直接自适应模糊控制方法。基于筒化了的T－S（Takagi-Sugeno）模糊推理规则,采用神经网络权值的联想式学习修正方法,对T－S模糊推理规则进行在线修正,给出了盯应的神经网络实现结构,从而实现了不需要建立受控对象模型的直接自适应模糊控制。对一混流式水轮机组的仿真控制实验结果证明了所提出方法具有设计简单、鲁棒性强的优点,能适应水轮机组在不同工况下的控制要求。     

基于火焰序列图像的煤粉燃烧稳定性判别

研究煤粉燃烧稳定性判别问题。对煤粉火焰图像进行了分析，提出了差分图像相对变化量作为特征参数来表征燃烧稳定性的方法，在此基础上提出了一种燃烧稳定性模糊判别方法。该方法将燃烧稳定性知识用语言形式描述出来，通过建立语言与特征参数之间的模糊关系，进而建立了特征参数与燃烧稳定性之间的模糊模式关系。试验表明：判别方法能有效地进行燃烧稳定性判别。这对实现燃烧状态自动监测，保障锅炉安全运行具有实际意义。图5参4     

A boiler-turbine system control using a fuzzy auto-regressive moving average (FARMA) model

This paper presents an application of an online self-organizing fuzzy logic controller to a boiler-turbine system of a fossil power plant. The control rules and the membership functions of the proposed fuzzy logic controller are generated automatically without using a plant model. A boiler-turbine system is described as a multi-input multioutput (MIMO) nonlinear system in this paper. Then, three single-loop fuzzy logic controllers are designed independently. Simulation shows robust results for various kinds of electric load demand changes and parameter variations of boiler-turbine system.     

Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system

This paper proposes a method of maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic systems. The system is composed of a boost converter and a single-phase inverter connected to a utility grid. The maximum power point tracking control is based on adaptive fuzzy logic to control a switch of a boost converter. Adaptive fuzzy logic controllers provide attractive features such as fast response, good performance. In addition, adaptive fuzzy logic controllers can also change the fuzzy parameter for improving the control system. The single phase inverter uses predictive current control which provides current with sinusoidal waveform. Therefore, the system is able to deliver energy with low harmonics and high power factor. Both conventional fuzzy logic controller and adaptive fuzzy logic controller are simulated and implemented to evaluate performance. Simulation and experimental results are provided for both controllers under the same atmospheric condition. From the simulation and experimental results, the adaptive fuzzy logic controller can deliver more power than the conventional fuzzy logic controller.     

基于ANFIS和SOM的抽水蓄能电站主变压器健康状态监测

针对抽水蓄能电站主变压器运行工况多变、状态信息复杂,难以实现健康状态监测的问题,提出基于自适应模糊推理系统(ANFIS)和自组织映射(SOM)的主变压器健康状态监测方法。该方法充分考虑主变压器运行工况多变,健康状态特征的高维和非线性特点,采用ANFIS消除运行工况对单状态特征参数异常监测精度的影响,并在此基础上利用SOM建立多特征融合的健康状态监测模型,采用最小量化误差(MQE)作为变压器健康状态监测指标。将该方法用于某抽水蓄能电站主变压器的健康状态监测,发现该方法可提前监测到主变压器健康状态的衰退,从而实现故障的早期预警,避免严重故障发生,并为运行和检修决策提供了依据。