铜冶炼气流干燥过程的混合气专家系统设计

针对气流干燥过程中水分难以稳定和充入一定量氮气后导致的操作人员人身安全问题,由现场生产工艺结合长期积累的专家经验知识,设计了一个氮气和稀释风的混合气专家系统;根据实际生产过程,提出了其产生式规则的知识表示形式,设计了气流干燥系统的专家知识库,通过正向推理机制,实现了专家系统的优化控制,实际应用表明,累计日消耗氮气量降低了1.1%,并且能确保回转窑内精矿不着火,既稳定了生产,又保障了工人的人身安全,具有工程实用性.     

燃油计量单元的地面模糊控制器设计

为了进行燃油计量单元地面试验,文中针对某型飞机燃油计量单元,设计出了一种基于高性能单片机的模糊控制器;控制器以80C58单片机为中央处理器,通过检测燃油计量单元输出口的燃油流量来实现步进电机的闭环控制,控制方式采用模糊算法,同时,设计按键模块用于步进电机工作方式的设定;仿真与实验证明,系统超调量为5%,稳态误差控制在±1%,控制速度快、精度高,满足设计要求。     

PLC在造气工艺中的应用

一、控制思想 小氮肥生产中造气工段分为六个阶段:吹风、回收、上吹、下吹、二上吹和吹净。工段任务是以煤、空气和水蒸汽为原料,制成半水煤气。 半水煤气所含成份为氢气、一氧化碳、氮气、二氧化炭、甲烷以及硫化氢等气体。在实际生产过程中,氢氮比调节是造气工段的主要操作。在生产过程中一般要求氢氮比控制在3.1～3.2左右。 氢氮比的调节是通过加氮(加空气)来调节的。若氢含量高,则适当增加氮空气量;若氢含量低,则适当减少氮空气量。调节的主要手段是通过测量氢气含量,产生一个过高或过低的信号来调节煤气发生炉空气输入管道控制阀,用以调节空气的输入量,进而调节氢氮比。     

基于自适应的大气相干长度测量仪控制系统设计

通过跟踪移动信标来测量大气湍流参数时,高精度的伺服控制技术是影响其测量精度的主要因素之一;在常规PID 控制的基础上,从自适应的角度出发,设计了一种适用于相干长度测量仪的且参数可自整定的控制器;当系统受扰动作用或系统运行状态变化时,在对系统不断辨识的基础上,依据性能指标,配置期望极点,实时调整控制器的参数值,实现系统的自适应,改善系统的鲁棒性;仿真及实验结果表明,采用自适应PID控制,在常值干扰下,系统的超调量减少26%,调节时间缩短1.28 s;跟踪20 mrad/s的目标时,系统的脱靶量峰峰值减小41.78%,稳态误差减小29.3%。相较于常规PID控制器,自适应PID控制器可减小超调量,缩短调节时间,优化跟踪性能,控制效果更好。     

可调谐激光气体水分传感器设计

针对低露点水分测量过程，特别是进行-80～-60℃范围露点测量时，缺少精度高、速度快、稳定性好、成本低的解决方案的问题，设计并实现了一种基于可调谐半导体激光吸收光谱(Tunable Diode Laser Absorption Spectroscopy, TDLAS)的气体水分传感器。该传感器采用1 392 nm可调谐分布式反馈(Distributed Feedbake, DFB)激光器，结合特殊设计的赫里奥特池，在吸收池体积为30 mL的情况下，光程达到了1.5 m。测量过程克服了空气背景干扰、管壁吸附等问题，实现了0.5～2 000μmol/mol的微量水检测，通过分段检测、多点标定的方式，保证了较宽量程范围内的测量准确度。采用氮气作为背景气进行试验，试验结果按露点温度计算，误差优于±0.32℃。该传感器测量重复性符合二级精密露点仪要求，可用于氮气和空气中的水分测量。     

复合式粉粒物料水分测量的新方法

针对粉粒物料水分在线连续测量存在的问题进行了分析，将快速失重法和电导法有机结合，对复合式水分测量方案进行了研究，通过实验得出了复合式水分测量模型．为粉粒物料水分测量提供了新的万法。     

基于软测量的醋酸精馏过程串级预测控制策略

针对醋酸精馏控制中,产品成分无法在线检测并且对产品质量采用温度间接控制存在控制精度低的问题,提出一种基于在线更新小波核函数极限学习机软测量的DMc预测控制策略,其中,在线更新的小波核函数极限学习机软测量实现了塔底醋酸浓度的实时检测,仿真结果表明,在线更新模型的预测精度比离线模型提高52%。将上述在线更新的软测量应用于塔底醋酸浓度闭环预测控制系统中,实现对塔底醋酸浓度的直接质量控制,该系统采用DMc作为醋酸浓度控制器,其输出量作为再沸器蒸汽流量控制器的设定值,与再沸器流量控制构成串级调节系统。控制系统仿真结果表明,该软仪表具有良好的在线预测性能,预测控制系统控制精度高、可以实现产品质量的卡边控制。     

一种新型水分活度自动检测仪的研制与应用

本文研制了一种能测量不同温度下的食品和医药水分活度的检测仪。仪器主要由半导体恒温器、模块电源、研华公司的数据采集模块以及温度、湿度传感器组成。恒温器中的温度可以调节并恒定在所需要的温度，恒温范围为-50℃～50℃，控制精度为0．1K。检测软件是利用VB6．0来编程，可以自动存储和打印检测的水分活度和温度数据。     

湿法炼锌生产中pH值的测量及自动控制

文中介绍了在湿法炼锌生产中pH值测量及实现方法，用单回路控制器调节液加入量，稳定了pH值，对生产起了重要作用。     

电力助动车控制器的原理、制作与调试

电力助动车无污染、低噪音,是最有发展前途的代步工具,相信不久将逐步取代甚至淘汰污染严重的燃油助动车。电力助动车的电气系统由蓄电瓶、电机及控制器组成。其中,控制器的功能较多,主要有: 1.连接电门旋钮和刹车手柄,实现对电机的功率调节(即车速调节)。     

基于软测量的自动配煤控制系统设计

针对配煤这一炼焦生产过程中的重要环节,其配比的准确性和配煤系统的可靠性将直接影响焦炭的质量和经济效益以及能否顺利推焦,某焦化厂由于所使用的皮带秤精度差,难以投入闭环控制,提出了一种基于多元线性回归的软测量技术,实现了配煤的准确称重;同时配煤过程被控对象具有非线性、时变、时滞,并且很难建立精确的数学模型,提出了基于专家知识的参数自整定模糊PID控制方法。这种基于软测量的模糊自整定方法在该厂配煤过程中成功应用,投运以来配煤合格率由原来的70%提高到95%,实现了稳定优化配煤,稳定焦炉生产,提高焦碳质量的目的。该方法具有广阔的应用前景和推广价值。     

Neural Network Controller Development and Implementation for Spark Ignition Engines With High EGR Levels

Past research has shown substantial reductions in the oxides of nitrogen (NO_x) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate control loop was designed for controlling EGR levels. The stability analysis of the closed-loop system is given and the boundedness of the control input is demonstrated by relaxing separation principle, persistency of excitation condition, certainty equivalence principle, and linear in the unknown parameter assumptions. Online training is used for the adaptive NN and no offline training phase is needed. This online learning feature and model-free approach is used to demonstrate the applicability of the controller on a different engine with minimal effort. Simulation results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller when implemented on an engine model that has been validated experimentally. For a single cylinder research engine fitted with a modern four-valve head (Ricardo engine), experimental results at 15% EGR indicate that cyclic dispersion was reduced 33% by the controller, an improvement of fuel efficiency by 2%, and a 90% drop in NO_x from stoichiometric operation without EGR was observed. Moreover, unburned hydrocarbons (uHC) drop by 6% due to NN control as compared to the uncontrolled scenario due to the drop in cyclic dispersion. Similar performance was observed with the controller on a different engine.     

基于专家-模糊PID控制的松散回潮出口水分控制系统设计

松散回潮属于大时滞系统,其出口烟叶水分控制所采用的带前馈-串级控制达不到理想的控制效果。在生产过程中需要根据经验手动修改加水系数,并没有真正实现完全自动化控制。提出了一种将专家系统、模糊推理和常规PID控制相互结合的新方法实现了松散回朝出口水分的控制,利用专家系统对加水系数进行自动决策;采用模糊推理方法分别对前室加水控制器与后室水分控制器的PID参数进行了在线自适应整定,实现了松散回潮出口水分控制的全自动化,提高了松散回潮出口水分的稳定性与精确性。     

Fuel gas blending benchmark for economic performance evaluation of advanced control and state estimation

A simulation of a fuel gas blending process and its measurement system is proposed as a benchmark test case for advanced control and state estimation. The simulation represents an industrial facility and employs a well-established software environment. The objective is to maintain four controlled variables within specified bounds while minimizing an economic performance index. The controlled variables are the fuel gas pressure and three measures of gas quality. Six feed gas flow rates may be adjusted to achieve the objective. Each has a limited availability.The benchmark consists of three reproducible scenarios, each a 46-h period during which 23 discrete upsets occur and the feed gas compositions vary gradually with time. A benchmark multi-loop feedforward–feedback structure is described, tested, and compared to an estimate of optimal performance. The operating cost provided by the benchmark controller is from 1.19 to 1.71 times higher than the estimated minimum.Readers are challenged to download the simulation model, benchmark controller and estimated optimal performance from the URL given in this paper, and to devise case studies of advanced state estimation and control strategies to better the proposed benchmark controller.     

焦炉加热过程无辨识自适应控制方法

针对焦炉火道温度直接影响焦炭质量和炉体寿命,而焦炉加热过程的大时滞、难以建立数学模型等特性造成焦炉加热过程火道温度控制十分困难的问题,提出一种具有专家修正的无辨识自适应控制方法。该方法不需要过程的数学模型,而是根据当前和过去的过程信息,基于专家规则估计过程未来的输出及变化趋势,对无辨识自适应控制的输出进行修正,获得过程控制所需的煤气流量设定值。仿真结果表明,该控制方法简单易行,有较好的鲁棒性,能比较好地控制焦炉加热过程火道温度。     

Integrated soft sensing of coke-oven temperature

This paper describes an integrated soft-sensing method of estimating the coke-oven temperature (COT). First, the characteristics of the coking process (change in direction of gas flow, coke-pushing series) are analyzed. Two variables are introduced to more precisely describe the COT: COTM is the COT on the machine side and COTC is the COT on the coke side. Next, that analysis is used to select the regenerating chambers where thermocouples should be installed; and the temperatures at the tops of the regenerating chambers on the machine side (TTRMs) and on the coke side (TTRCs) are used as auxiliary variables in soft sensing. Then, two types of linear-regression (LR) models are built, one in 12 variables and one in one variable; and supervised distributed neural networks (SDNNs) are also built to estimate COTM and COTC. The LR model in 12 variables and the SDNN models are integrated to accurately describe the nonlinear relationship between COTM (COTC) and the TTRMs (TTRCs) under normal conditions. Supervised clustering is used to divide the sample space into several subspaces, and a neural network is built for each one. The LR model in one variable [the average TTRM (TTRC)] is employed to estimate COTM (COTC) for abnormal conditions. An expert coordinator balances the outputs of these models. A model adaptive unit periodically updates the parameters of the soft-sensing model to reflect changes in the operating conditions and environment. Finally, the model was implemented in an optimization and control system for the COT. The results of actual runs demonstrate the effectiveness of the model.     

造纸过程水分智能控制

针对造纸过程的复杂性、工艺特点及要求，本文对造纸过程的水分控制，提出模糊控制和专家系统结合的智能控制方法。实践证明该控制器满足了造纸过程对水分的工艺要求，且具有良好的鲁棒性。     

基于KPCA-LS-SVM的工业锅炉烟气含氧量预测

排烟含氧量是评价燃烧过程好坏和锅炉优化运行的重要指标,也是调节最佳风煤比的主要依据。针对工业锅炉氧量计使用受限的问题,提出一种混合的软测量方法:。为了提高烟气含氧量的软测量预测精度,本文分析与烟气含氧量有关的锅炉运行变量,从中确定8个,并采用核主成分析法进行参数处理,整合冗余,降低维数。经处理后得到的6个主成分,其累计贡献率达95.522%,以此作为最小二乘支持向量机软测量模型的输入。在此基础上,通过划分网格来改进交叉实验法,进而优化最小二乘支持向量机的2个参数。经优化得到的误差参数γ和径向基核函数参数σ~2分别为90.3和239.6,模型具有较高的训练精度。最后对某循环流化床锅炉进行建模仿真,利用采集的数据,分别建立最小二乘支持向量机、核主成分分析的最小二乘支持向量机和BP神经网络3种模型。应用3种模型对烟气含氧量进行预测,并采用3个模型性能指标进行对比分析。结果:表明,基于核主成分分析的最小二乘支持向量机的工业锅炉烟气含氧量模型,在小样本条件下学习更加有效,建模采样过程更快,预测精度更高。该模型有助于实现工业锅炉烟气含氧量在线软测量。     

Adaptive internal model control with application to fueling control

This paper presents an adaptive internal model controller for stable but not necessarily minimum-phase SISO plants and its application to the air/fuel ratio control system of a spark-ignited engine. The internal model of the controller is formulated in an output-error structure that can be adapted by using standard adaptive laws. The method is applied to an air/fuel ratio control system with a reduced-order internal model and unknown sensor dynamics. Experiments on an engine test bench demonstrate the capability of the adaptive controller to recover the performance and robustness properties of the control system in the case of an aged oxygen sensor.     

烟叶复烤生产线排潮率的软测量工程实现研究

烟叶复烤生产线加热区的排潮率是反映烟叶中含水多少的关键参数之一,但难以直接在线测量。为此,本论文将软测量技术应用于烟叶的复烤过程,以实现排潮率的在线软测量。论文采用多冗线一降回归分析法,建立了排湖率的软测量模型并对拟合和预测结果进行了分析,农叫其软测量模型具有较好的预测效果。同时,将排潮率的软测量模型与力控6．0组态软件相结合,实现了烟叶复烤生产线干燥区的实时监控。