Chapter 1 Review of the Advancement in Thickness Control Technology
1.1 Control strategy of hydraulic servo system
1.1.1 Current status and development trend of recent control strategy applications
1.1.2 Characteristics of recent electro hydraulic servo systems and requirements for control strategies
1.1.3 Nonlinear and exact linearized optimal control of hydraulic servo systems
1.2 Fundamental formula of rolling mathematical model
1.2.1 Elastic deformation and spring equation of the stand
1.2.2 Plastic deformation of rolled parts with plasticity equation
1.2.3 Rolling force model
1.2.4 Causes of thickness fluctuations
1.3 Traditional thickness control strategies
1.3.1 Hydraulic position control
1.3.2 Dynamic settings
1.3.3 Quick monitoring
1.3.4 Taper head
1.3.5 Feedforward AGC
1.3.6 Feedback AGC
1.3.7 Monitor AGC
1.3.8 Mass flow AGC
Chapter 2 Hydraulic Gap Control of Rolling Mill
2.1 Adaptive compensation of hydraulic servo control system
2.1.1 Introduction
2.1.2 Hydraulic cylinder
2.1.3 Servo valve
2.1.4 Rate of change in pressure equation
2.1.5 Step response analysis
2.1.6 Conclusion
2.2 Hydraulic gap control of rolling mill based on self tuning fuzzy PID
2.2.1 Introduction
2.2.2 Modeling of the HGC system
2.2.3 Model identification of the HGC system
2.2.4 Fuzzy PID design
2.2.5 Simulation and field test results
2.2.6 Conclusion
2.3 Active disturbance rejection synchronous control for both sides of the hydraulic servo position system of the rolling mill
2.3.1 Introduction
2.3.2 System description and problem posing
2.3.3 Design of active disturbance rejection synchronous controller
2.3.4 Simulation and experiment research
2.3.5 Conclusion
Chapter 3 Thickness Control of Hot Strip Mill
3.1 Online thickness prediction based on kernel partial least squares
3.1.1 Introduction
3.1.2 Algorithm introduction
3.1.3 Models and applications
3.1.4 Conclusion
3.2 Online thickness prediction of hot rolled strip based on ISSA OSELM
3.2.1 Introduction
3.2.2 Basic algorithm
3.2.3 Data processing and online prediction model design
3.2.4 Algorithm simulation and performance verification
3.2.5 Conclusion
3.3 Online segmented thickness prediction based on IBA XGBoost
3.3.1 Introduction
3.3.2 Materials and methods
3.3.3 Online prediction model design
3.3.4 Experiment on thickness prediction
3.3.5 Discussion
3.3.6 Conclusion
3.4 An online algorithm for roll eccentricity compensation
3.4.1 Introduction
3.4.2 Compensation algorithm
3.4.3 Control concept
3.4.4 Applications
3.4.5 Conclusion
3.5 Expert PI controller with dead time compensation of monitor AGC
3.5.1 Introduction
3.5.2 Filtered Smith predictor
3.5.3 FSP for monitor AGC
3.5.4 Expert PI controller design
3.5.5 Applications
3.5.6 Conclusion
Chapter 4 Thickness Control of Plate Rolling Mill
4.1 Thickness control system for medium and heavy plates
4.1.1 Overview
4.1.2 System scheme design
4.1.3 Automation system structure and hardware configuration
4.1.4 Basic automation level (L1) functionality
4.1.5 Process automation level (L2) functionality
4.1.6 Conclusion
4.2 Research and application on controlled rolling and cooling for medium and heavy plates
4.2.1 Overview
4.2.2 Process overview
4.2.3 Interstand cooling mathematical model
4.2.4 Hierarchical computer control system
4.2.5 Field application and conclusion
4.3 Rolling force prediction in heavy plate rolling based on uniform differential neural network
4.3.1 Introduction
4.3.2 Mathematical model of plate rolling
4.3.3 Differential evolution algorithm
4.3.4 Rolling force prediction model based on uniform differential neural
展开
