矿井提升计算机模糊控制系统

本文结合国内多数矿井的实际情况，采用具有动态响应特性好的模糊控制方法，设计出了根据矿井井底主煤仓煤量的多少来对矿井提升进行自动控制的计算机模糊控制系统。文章详细介绍了矿井提升计算机模糊控制系统的控制原理、模糊控制器的设计及控制系统的设计等。     

基于多模型切换的过热汽温智能控制

针对火电厂过热汽温控制系统具有大迟延、时变等特点,常规控制难以取得满意的控制效果,提出了基于多模型切换的过热汽温智能控制方法。仿真结果表明,过热汽温控制的动态特性明显得到改善。     

燃煤锅炉过热蒸汽温度模糊PI控制系统的研究

锅炉过热汽温具有大惯性、大滞后的特点,并且动态特性随机组负载变化而变化,运行过程中扰动多、难控制。文章针对这种情况,研究了Fuzzy-PI复合控制算法,并针对某火电厂燃煤锅炉过热蒸汽温度进行了仿真研究。在分析蒸汽温度系统工作过程、调节对象及其动态特性的基础上,构建了系统的结构模型;在对火电厂过热汽温控制对象特点分析的基础上,保留串级控制抗内扰的性能,结合模糊控制动态特性好的特点,提出了一种复合模糊串级控制设计方法。该方法综合了模糊控制和PI控制的优点,增强了系统的鲁棒性,仿真研究结果也证明该方法有效。     

基于自寻优-采样控制的火电厂磨机负荷控制系统的研究

针对火电厂球磨机负荷系统,提出了自寻优-采样PI相结合的双层控制策略.采用PLC和工业控制计算机构成一个小型的DCS系统.所开发的球磨机负荷控制系统已经在新疆石河子天业火电厂投入实际运行,控制性能良好,节能效果显著.     

火电厂多代理控制系统

针对火电厂非线性、多变量和多控制目标的特点,设计了一个火电厂多代理控制系统(PPMACS).在PP MACS中,前馈控制代理(FFCAs)采用神经模糊系统进行决策,反馈控制代理(FBCAs)采用基于遗传算法的模糊系统进行决策.优化任务分解代理(OTDAs)通过一个优化代理和一个分解代理来进行多目标优化分解PPMACS的任务.协调代理根据运行条件协调PPMACS的各个代理.仿真结果显示了火电厂多代理控制系统能够实现火电单元机组的多目标运行和大范围负荷跟踪.神经网络、模糊逻辑和遗传算法是PPMACS中的智能代理进行决策的有效工具.     

自适应模糊PID控制在火电厂给水加药中的应用

高参数、大容量机组成为火电厂发展的趋势,为了保证机组的安全经济运行,对热力系统汽水指标的控制提出了更严格的要求.而调节锅炉给水水质的加药过程具有大滞后、非线性、时变等特性,常规的控制方法难以获得满意的控制效果.针对火电厂给水加药系统的特点,将模糊控制引入到锅炉给水加药控制系统中,提出将模糊控制与常规PID控制相结合的思路,设计自适应模糊PID控制模型,仿真研究了控制器的动态性能.仿真结果表明,该方法具有较好的动态品质和调节精度.现场运行实验结果也表明了该方法的有效性.     

基于改进的PSO算法的球磨机PID神经网络控制系统

球磨机制粉系统是一个复杂的多变量系统,具有强耦合、非线性、大迟延、慢时变等特点,很难建立精确的数学模型,采用常规的控制策略难以获得满意的控制效果。针对上述问题,在对球磨机制粉系统动态特性进行分析的基础上,提出了一种不依赖于被控对象数学模型的多变量PID神经网络解耦控制策略;为进一步提高控制器性能,利用一种改进的PSO算法对PID神经网络的权值初值进行离线优化训练,然后采用BP算法对权值进行在线调整,避免网络陷入局部极小值,保证了系统不会出现大的超调和震荡。仿真结果表明,该策略可以保证球磨机控制系统有大范围的鲁棒性和适应性,能较好地解决球磨机制粉系统的耦合性、时变性等问题,具有优良的解耦机制和控制品质。     

燃煤锅炉过热蒸汔温度模糊PI控制系统的研究

锅炉过热汽温具有大惯性、大滞后的特点，并且动态特性随机组负载变化而变化，运行过程中扰动多、难控制。文章针对这种情况，研究了Fuzzy-PI复合控制算法，并针对某火电厂燃煤锅炉过热蒸汽温度进行了仿真研究。在分析蒸汽温度系统工作过程、调节对象及其动态特性的基础上，构建了系统的结构模型；在对火电厂过热汽温控制对象特点分析的基础上，保留串级控制抗内扰的性能，结合模糊控制动态特性好的特点，提出了一种复合模糊串级控制设计方法。该方法综合了模糊控制和PI控制的优点，增强了系统的鲁棒性，仿真研究结果也证明该方法有效。     

基于模糊自整定PID的主汽温串级控制系统的设计

火电厂主汽温具有大惯性、大迟延和时变特性等特性,采用常规的PID串级控制难以获得满意的控制效果.为此,提出一种基于模糊自整定PID控制器的串级控制系统,该系统将模糊控制、PID控制和串级控制三者有机地相结合,提高了主汽温控制系统的控制品质.仿真结果表明：系统超调量、调节时间和抗干扰能力明显优于常规的PID串级控制.     

球磨机灰色预测无模型自适应控制策略

球磨机负荷控制系统是一个具有大时滞、强时变性、强非线性及多变量与强耦合等特性的复杂系统。为了更好地克服球磨机负荷控制系统中存在的大滞后和不确定性等问题,提出了灰色预测无模型自适应控制(MFAC)策略。在控制系统下,分别采用PID、灰色预测PID、MFAC及灰色预测MFAC进行控制仿真分析。实际应用验证了该策略的可行性与合理性,表明了灰色预测无模型控制策略具有良好的控制性能和实用价值。     

基于模糊内模控制的球磨机系统的研究

球磨机系统具有多变量、强耦合、长时滞以及生产工况变化大等特点,采用常规控制策略很难达到控制目标。针对该问题,文章提出了一种基于模糊内模控制的球磨机系统的设计方案,分析了球磨机工作原理,建立了其数学模型,详细介绍了球磨机系统的解耦分析,最后给出了球磨机模糊内模控制器的设计方法。仿真结果表明,基于模糊内模控制的球磨机系统具有良好的解耦能力,鲁棒性强,能够较好地解决球磨机系统的时变性、耦合性和延迟性问题,具有一定的工程应用价值。     

Intelligent optimal control system for ball mill grinding process

Operation aim of ball mill grinding process is to control grinding particle size and circulation load to ball mill into their objective limits respectively, while guaranteeing producing safely and stably. The grinding process is essentially a multi-input multi-output system (MIMO) with large inertia, strong coupling and uncertainty characteristics. Furthermore, being unable to monitor the particle size online in most of concentrator plants, it is difficult to realize the optimal control by adopting traditional control methods based on mathematical models. In this paper, an intelligent optimal control method with two-layer hierarchical construction is presented. Based on fuzzy and rule-based reasoning (RBR) algorithms, the intelligent optimal setting layer generates the loops setpoints of the basic control layer, and the latter can track their setpoints with decentralized PID algorithms. With the distributed control system (DCS) platform, the proposed control method has been built and implemented in a concentration plant in Gansu province, China. The industrial application indicates the validation and effectiveness of the proposed method.     

Load control of ball mill by a high precision sampling fuzzy logic controller with self‐optimizing

A self‐optimizing, high precision sampling fuzzy logic controller for keeping a ball mill circuit working stably and efficiently is proposed in this paper. The controller is based on fuzzy logic control strategy, and a fuzzy interpolation algorithm is presented to improve the control precision. The final output of the controller is calculated through the interpolation calculation of the observation and its neighboring antecedents, and the interpolation weight coefficients are obtained according to a fuzzy inference algorithm. In the proposed controller, the sampling control strategy is used to deal with a large delay time and a controller set value which can be adjusted by a self‐optimizing algorithm, which can overcome the time‐varying characteristic. Simulation results verify that the controller can control the ball mill circuit effectively and have higher control quality. Field service results also verify that the controller can successfully optimize the control of ball mill circuit. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

优化隶属度函数在中储式磨煤机中的应用

要保证磨煤机的最佳运行工况,就要使磨煤机的负荷,温度,入口负压稳定在最佳值附近,传统的模糊控制在磨煤机系统中虽运用广泛,但是完全基于专家经验的控制很难保证系统运行在最佳状态下,因此提出了采用遗传算法优化模糊控制隶属度函数的方法控制磨煤机的运行,解决了由于专家经验的不精确性带来的不足.     

A neural intellectual decoupling control strategy for a power plant ball miller

1 Introduction As an important auxiliary equipment, the ball mill cannot be operated automatically and e?ectively in the majority of domestic and international power plants. When it is automated, it can initially work well, but will deviate from its optimum work condition after a while and cease to be functionally e?ective. The ball mill is a time-changing system of MIMO, which is strong coupling, and long delay. It is di?cult to de- scribe such a system with a precise mathematic model, thou…     

基于神经网络的球磨机出力软测量模型研究

球磨机出力检测和控制是球磨机自动控制的重要内容,然而,目前在实际生产过程中,球磨机出力缺少有效可靠的检测手段,因此很难实现优化控制.结合基于神经网络的软测量和混沌信息处理技术两者的优点,建立球磨机出力软测量模型.该模型不仅能预估稳态下球磨机出力,且对动态过程中球磨机出力的在线估计也切实有效,从而为球磨机的出力监测、给煤...     

Multiple models and neural networks based decoupling control of ball mill coal-pulverizing systems

Using a ball mill coal-pulverizing system as a motivating/application example, a class of complex industrial processes is investigated in this paper, which has strong couplings among loops, high nonlinearities and time-varying dynamics under different operation conditions. Focusing on such processes, an intelligent decoupling control method is developed, where the effects of nonlinearities are dealt with by neural network compensations and coupling effects are handled by specifically designed decoupling compensators, while the effect of time-varying dynamics is treated by a switching mechanism among multiple models. The stability and convergence of the closed-loop system are analyzed. The proposed method has been applied to the ball mill coal-pulverizing systems of 200 MW units in a heat power plant in China. Application results show that the system outputs are maintained in desired scopes, the electric energy consumption per unit coal has been reduced by 10.3%, and the production rate has been increased by 8%.     

A Clustering-analysis-based membership functions formation method for fuzzy controller of ball mill pulverizing system

This paper proposes a clustering-analysis-based membership functions formation method for fuzzy controller of ball mill pulverizing system. An improved density-based clustering algorithm is presented to detect the clusters in the field database and the clusters are agglomerated or divided to form the new clusters according to the proximity or the dissimilarity between objects. Then, the new clusters are projected into the domains of the control variables to form the intervals, and the membership functions are established based on the intervals and the projections of the centroids of the clusters. The experiments results verify that the performance of our membership functions formation method is better and the fuzzy controller designed by our method has higher control quality. In addition, the fuzzy controller has been put into practice and the field data verify the effectiveness of the fuzzy controller.     

火电厂球磨机非线性自适应控制

建立了球磨机特征模型,分析了运行调节需求,设计了以给煤量非线性自适应PID控制为主体,多种控制方式相结合的球磨机控制系统。该系统由磨风量控制、磨给煤量控制和风煤协调控制三部分构成,合理组合了非线性自适应PID控制、解耦控制、比值控制和仿人控制算法优势。工程应用表明,该控制系统能够解决球磨机运行优化和控制优化的双重问题,控制系统鲁棒性强,具有工况自适应能力。