复杂冶金过程智能控制(英文版)

Contents1 Introduction 11.1 Complex Metallurgical Processes 11.2 Modeling， Control， and Optimization of Complex Metallurgical Processes 31.2.1 Modeling 31.2.2 Control 41.2.3 Optimization 61.3 Intelligent Control and Optimization Methods 61.3.1 Neural Network Modeling 61.3.2 Fuzzy Control 111.3.3 Expert Control 121.3.4 Decoupling Control 161.3.5 Hierarchical Intelligent Control 191.3.6 Intelligent Optimization Algorithms 211.4 Outline of This Book 29References 302 Intelligent Optimization and Control of Raw Material Proportioning Processes 332.1 Process Description and System Configuration 362.1.1 Process Description and Characteristic Analysis 362.1.2 Control Architecture 402.2 Intelligent Optimization and Control of Coal Blending Process 412.2.1 Quality-Prediction Models for Coal Blend 412.2.2 Quality-Prediction Models for Coke 432.2.3 Rule Models 452.2.4 Determination of Target Percentages Based on Rule Models 462.2.5 Determination of Target Percentages Based on Simulated Annealing Algorithm 492.2.6 Tracking Control of Target Percentages 512.3 System Implementation for Coal Blending Process 522.3.1 System Configuration and Implementation 522.3.2 Results of Actual Runs of Coal Blending Process 532.4 Intelligent Integrated Optimization System for Proportioning of Iron Ore in Sintering Process 542.4.1 Cascade Integrated Quality-Prediction Model for Sinter 562.4.2 Verification of Quality-Prediction Model 632.4.3 Optimization Model of Proportioning 652.4.4 Optimization Method 682.4.5 Verification of Optimization Algorithms 732.5 System Implementation for Proportioning of Iron Ore in Sintering Process 772.5.1 System Configuration and Implementation 772.5.2 Results of Actual Runs in Sintering Process 792.6 Conclusion 80References 813 Intelligent Optimization and Control of Coking Process 833.1 Characteristic Analysis and System Configuration 853.1.1 Process Description 863.1.2 Analysis of Characteristics 883.1.3 Control Requirements 903.1.4 System Configuration 913.2 Integrated Soft Sensing of Coke-Oven Temperature 933.2.1 Choice of Auxiliary Variables and Measurement Points 933.2.2 Structure of Soft-Sensing Model for Coke-Oven Temperature 933.2.3 Integrated Linear Regression Model 953.2.4 Supervised Distributed Neural Network Model 973.2.5 Model Adaptation 1003.3 Intelligent Optimization and Control of Coke-Oven Combustion Process 1013.3.1 Configuration of Hybnd Hierarchical Control System 1013.3.2 Determination of Operating State 1033.3.3 Design of Coke-Oven Temperature Controller 1053.3.4 Design of Controller for Gas Flow Rate 1103.3.5 Design of Air Suction Power Controller 1113.4 Operation Planning and Optimal Scheduling of Coking 1123.4.1 Analysis of Operations Planning and Optimal Scheduling of Coking 1123.4.2 Configuration of Optimal Scheduling 1143.4.3 Optimal Scheduling of Operating States 1153.5 System Implementation and Results of Actual Runs 1223.5.1 System Implementation 1233.5.2 Results of Actual Runs for Integrated Soft Sensing of Coke-Oven Temperature 1243.5.3 Results of Actual Runs for Intelligent Optimization and Control of Coke-Oven Combustion Process 1243.5.4 Results of Actual Runs for Coke-Oven Operation Planning and Optimal Scheduling 1293.6 Conclusion 130References 1314 Intelligent Control of Thermal State Parameters in Sintering Process 1354.1 Process Description and Characteristics Analysis 1354.1.1 Description of Sintering Process 1354.1.2 Characteristic Analysis of Thermal State Parameters in Sintering Process 1364.1.3 Control Requirements 1394.2 Intelligent Control of Sintering Ignition Process 1404.2.1 Control System Architecture 1404.2.2 Intelligent Optimization and Control Algorithm 1414.2.3 Subspace Modeling of Sintering Ignition Process 1424.2.4 Periodic Disturbance Rejection Using Equivalent-Input-Disturbance Estimation 1474.2.5 Experimental Simulation 1514.3 Intelligent Control System for Bum-Through Point 1554.3.1 Control System Architecture 1554.3.2 Soft Sensing and Prediction of Bum-Through Point 1574.3.3 Hybrid Fuzzy-Predictive Controller 1614.3.4 Bunker-Level Expert Controller 1654.3.5 Coordinating Control Algorithm 1654.4 Industrial Implementation and Results of Actual Runs 1684.4.1 Industrial Implementation 1684.4.2 Results of Actual Runs 1694.5 Conclusion 172References 1735 Intelligent Decoupling Control of Gas Collection and Mixing-and-Pressurization Processes 1775.1 Process Description and Characteristic Analysis 1805.1.1 Description and Analysis of Gas Collection Process 1805.1.2 Description and Analysis of Gas Mixing-and-Pressurization Process 1835.2 Intelligent Decoupling Control of Gas C