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 network
The 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 prent, 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 posss 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 propos 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 techniqueBad 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 propod, 2020高考真题试卷
which includes the three part of basic concept, integrated structure and system building. It is divided into three basic structures of ries 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 propod.(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
when
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 istablished with combination of the neural network model of technics parameters and the neural network model of time ries, 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 ries, 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
prettygoodthe 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 bad on state predictive models. The whole optimization control algorithm posss 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 arching , 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 propod, by using the improved BP neural network.The penalty function method is ud to transform the muti-target-constrained optimization problem to unlimited optimization problem. The parallel arching bad on fuzzy clustering is ud to realize the raw optimization, while the elitist prerved simple genetic algorithm and chaos optimization are ud to realize the accurate optimization. .
In this paper, with the Pb-Zn sintering process of Imperial Smelting Process(ISP) in ShaoguanSmeltery Works as study object, the design and implementation of y XL Distributed Control System(DCS) of sintering process is
雅思考试内容fulfilled as well as the development of Optimal Control System. Bad on the analysis of mechanism of sintering process, the key factors and procedures for production and quality of sintering are discusd. 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 compod of state parameters module and optimal control module. State parameters module includes prediction models for veral 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 bad on principle component analysis and clustering arch will function for optimization. This algorithm makes no request for accurate analytical model and maintains arch efficiency and lf-adjusting performance by an optimal parameter t 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 stabilit好看的英语单词
y and production benefit of sintering process obviously. In the end of the disrtation, the achievements are concluded and further rearch suggestions are discusd.
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 ShaoguanSmeltery is investigated, which is to solve the prediction modeling and optimization problems of permeability and BTP. As to permeability, At first, bad 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
加拿大留学预科>pets是什么the two sub-models with weighting method of sample memberships. As regard to BTP, the paper prents an approach that integrates two models to predicting the BTP. The first method us neural network to predict the BTP ; The cond method us metallurgical and control expert knowledge and skilled operator experiences of the sintering process. Two results are combined by u 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 re
sults 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 decread and the quality of sintering process can be ensured if the optimal control strategy areadopted.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. propod technical knowledge of ISP sintering process and character of sintering process with emphas on prent 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 bad on fuzzy-classification with expert rules. establisheda integrated model witch was combined by ANN model and fuzzy logical model for predicting the BTP bad on Optimal Combination Algorithm. discusd the optimal control of permeability and BTP, the results of optimization were ud 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
迷路的英文铅锌冶炼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、氧束手无策英语>ccx
