外文翻译---铅锌烧结过程智能集成优化控制技术及其应用研究.docx

附录a：study on intelligent integrated optimal control technique and application to lead-zinc sintering process keywords: lead-zinc sintering process, intelligent control,integrated modeling, integrated optimization, neural networkthe lead-zinc imperial smelting process is one of the modern advanced methods of the lead-zinc smelting utilizing neoteric burning technology. as an important loop of isp, imperial updrafted-sintering process has a direct influence on state of the smeltering furnace and output of lead-zinc. at present, for the laggard control techniques and the low-level automatization, the process optimal control has become the key problem to restrict the output and quality of the sinter. since lead-zinc sintering process possesses the characteristics such as strong nonlinear, strong coupling, uncertain, time-varying, long time-delay, multi-constrained, neither the traditional control theory not simple intelligent technique can satisfy the demands of multi-target global optimal control. thus, the thesis proposes an intelligent integrated optimal control technique, which solves the optimal control of state and output-quality in lead-zinc sintering process. the main study achievements include:(1) intelligent integrated optimal control techniquebased on the analysis of the characteristics of the lead-zinc sintering process and control problems, the basic frame of the intelligent integrated optimal control is proposed, which includes the three part of basic concept, integrated structure and system building. it is divided into three basic structures of series intelligent integrated, parallel intelligent integrated and nesting intelligent integrated. thus, the key problems and techniques of the informatization, modelizaion, control optimization and industrialization to establish the intelligent integrated optimal control system are proposed.(2) state optimal control technique of fuzzy expert control and clustering grid algorithmaimed at the state real-time measure problem, the model of btp and the temperature distribution model of waste gas are established. aimed at the character of long time-delay, with the adoption of fuzzy clustering method, the integrated predictive model of synthetical permeability isestablished with combination of the neural network model of technics parameters and the neural network model of time series, and the integrated btp predictive model is established with combination of the neural network model of technics parameters and the grey theory model of time series, which improves the precision of state predictive model effectively.the lead-zinc sintering process has a large number of fuzzy and uncertain informations and qualitative expert operation rules. the sintering materials are divided into three types of high quality, mid quality, low quality , and for the different-quality materials the state optimal values are decided respectively, by using fuzzy expert optimization rules. the strategy of fuzzy expert and clustering grid are adopted in order to find the state optimal control parameters, according to ahead predictive errors. the fuzzy expert control has the function to simulate the human experts optimization control, while the clustering grid control is an accurate strategy based on state predictive models. the whole optimization control algorithm possesses industrial validity and higher control precision, which resolves the state optimization control problem with multi-constrained, uncertain, nonlinear, characteristics.(3) output-quality optimal control technique of clustering searching , genetic algorithm and chaos optimizationaimed at the long time-delay characteristic and the measure problem of quantity and quality of sinters, the predictive models of quantity, pb content, zn content, s content, sio2 content, and cao content of sinter are proposed, by using the improved bp neural network.the penalty function method is used to transform the muti-target-constrained optimization problem to unlimited optimization problem. the parallel searching based on fuzzy clustering is used to realize the raw optimization, while the elitist preserved simple genetic algorithm and chaos optimization are used to realize the accurate optimization. .in this paper, with the pb-zn sintering process of imperial smelting process(isp) in shaoguan smeltery works as study object, the design and implementation of y xl distributed control system(dcs) of sintering process is fulfilled as well as the development of optimal control system. based on the analysis of mechanism of sintering process, the key factors and procedures for production and quality of sintering are discussed. designing this computer control system must take process stabilization and parameter optimization into account. u xl dcs is a powerful and competitive system with easy extension, perfect control, convenient data dealing, concentrated operation, friendly interface, simple and canonical installation, expedient debugging and safe and reliable running. by system configuration and software development for control, all important parameters in sintering process are stabilized and key procedures such like mineral blending and watering are insured for stability and precision. the optimal control system of sintering process is composed of state parameters module and optimal control module. state parameters module includes prediction models for several production targets such as synthesized permeability, yields of agglomerate, sulfur content and plumbum content in agglomerate. the sintering state is judged and evaluated by the prediction results. if it is not good enough, optimal control module based on principle component analysis and clustering search will function for optimization. this algorithm makes no request for accurate analytical model and maintains search efficiency and self-adjusting performance by an optimal parameter set derived from process data, which is proved to be effective.by practical running of dcs, a prominent tracing performance is gained and variation of parameters is limited in a small range, which enhance stability and production benefit of sintering process obviously. in the end of the dissertation, the achievements are concluded and further research suggestions are discussed.in the paper, an integrated modeling and optimization method for the pb-zn sintering process states (including permeability and burning through point ) of imperial smelting process (isp) in shaoguan smeltery is investigated, which is to solve the prediction modeling and optimization problems of permeability and btp. as to permeability, at first, based on empirical knowledge, the input samples space is fuzzy-classified into low-temperature subspace and high-temperature subspace on the basis of the highest temperature of the sintering machine, then corresponding two sub-models are established. finally, the predicative model is obtained by synthesizing the two sub-models with weighting method of sample memberships. as regard to btp, the paper presents an approach that integrates two models to predicting the btp. the first method uses neural network to predict the btp ; the second method uses metallurgical and control expert knowledge and skilled operator experiences of the sintering process. two results are combined by use of optimal combination algorithm as general modeling results of the btp. according to the actual circumstances of the sintering process ,an expert _religion optimal control strategy of sintering states witch regards permeability as center is advanced. through the experts rules, the predictive results of sintering states are applied to guide the optimal control manipulation. simulation results show that the sintering process will be stable, the productivity will be improved, the cost of the sintering process will be decreased and the quality of sintering process can be ensured if the optimal control strategy are adopted.the paper is organized as follows. briefly introduced technical process of isp pb-zn smelting method and pointed out the significance and necessity of the subject. proposed technical knowledge of isp sintering process and character of sintering process with emphases on present problems in sintering process control and problems studied in this paper and the whole designation framework. established a distributed ann model for predicting the permeability based on fuzzy-classification with expert rules. established a integrated model witch was combined by ann model and fuzzy logical model for predicting the btp based on optimal combination algorithm. discussed the optimal control of permeability and btp, the results of optimization were used to instruct the producing.附录b：铅锌烧结过程智能集成优化控制技术及其应用研究关键词：铅锌烧结过程,智能控制,集成建模,集成优化,神经网络铅锌冶炼isp工艺是近代火法炼铅锌的先进方法之一，密闭鼓风烧结过程作为其中的一个重要流程，直接影响到熔炼炉炉况和铅锌产量。目前铅锌烧结过程控制技术落后、自动化水平低，过程优化控制成为制约烧结矿产量质量的一个瓶颈。针对具有强非线性、强耦合性、不确定性、时变、大滞后、多约束特点的铅锌烧结过程，采用传统的控制理论或单一的智能化技术难以满足多目标全局优化控制要求，本文提出一种智能集成优化控制技术，有效解决了铅锌烧结过程状态优化控制和产量质量优化控制问题。论文的主要研究成果包括： (1) 智能集成优化控制技术 基于铅锌烧结过程特性和控制问题分析，提出了智能集成优化控制技术基本框架，包括基本概念、集成结构和系统实现三部分内容。从集成形式上划分为串联智能集成、并联智能集成和嵌套智能集成三种基本结构，提出了建立智能集成优化控制系统的信息化、模型化、控制优化和工业化关键问题与技术。 (2) 模糊专家聚类网格状态优化控制技术 针对状态实时检测问题，建立了烧穿点软测量模型、烟气温度场分布模型；针对过程大滞后特性，采用模糊分类方法，将工艺参数神经网络模型与时间序列神经网络模型集成，建立了综合透气性预测模型，将工艺参数神经网络模型与时间序列灰色理论模型集成，建立了烧穿点预测模型，有效地提高了状态预测精度。 在铅锌烧结过程中存在有大量模糊的不确定性信息，专家操作经验往往以一种定性描述形式出现。采用模糊专家优化规则将混合料分为高品位矿、中品位矿和低品位矿，针对不同品位的混合料进行不同的状态优化值设定。采用模糊专家控制结合聚类网格控制的策略，根据超前预测误差获取状态优化控制参数，模糊专家控制可以模拟人类专家的优化操作，聚类网格控制则是基于状态集成预测模型的精确控制，整体优化控制算法具有工业有效性和较高的控制精度，解决了铅锌烧结过程中具有多约束、不确定性和非线性特点的状态优化控制问题。 (3) 聚类搜索遗传混沌产量质量优化控制技术 针对过程大滞后和产量质量测量问题，采用改进的bp神经网络，中南大学博士学位论文摘要建立了铅锌烧结矿产量、含铅量、含锌量、含硫量、二氧化硅含量、氧化钙含量预测模型。 用罚函数法将多目标约束优化问题转化为无目标约束优化问题，采用基于模糊聚类的并行搜索进行粗优化，采用最优保存简单遗传混沌优化算法进行精确优化，整体优化控制算法具有全局收敛性和工业有效性，解决了铅锌烧结过程中具有多目标约束强非线性特点的产量质量优化控制问题。 (4)智能集成优化控制系统 采用p xl集散控制系统和管理信息系统实现了底层自动化和高层信息管理，在信息化、模型化和控制优化的基础上建立了智能集成优化控制系统，通过对状态短期优化控制策略和产量质量长期优化控制策略的智能协调，实现了铅锌烧结过程多目标全局优化控制。 通过应用铅锌烧结过程智能集成优化控制技术，从整体上提高了铅锌烧结工艺过程优化控制水平，有效地抑制了烧穿点和透气性波动，产量质量得到了提高，同时加强了信息管理能力，降低了工人的劳动强度，取得了显著的经济效益和社会效益。同时也为复杂工业过程优化控制提供一套实用的。本文以韶关冶炼厂isp铅锌烧结过程为对象，设计和实现了烧结过程xl集散控制系统，设计和开发了烧结过程优化控制系统。首先在研究烧结过程机理的基础上，分析了影响烧结产量质量的关键因素和关键工艺环节，在计算机控制系统的设计中主要从系统稳定化控制和参数优化设定两