Dynamic Control Arithmetic and Modeling of Secondary Cooling System for ROKOP Billet Continuous Casting

A dynamic control arithmetic and mathematic model of secondary cooling system for ROKOP billet concasting has been developed in view of the changes of casting speed during concasting process and the high fluctuation of surface temperature due to the use of static control method. By means of computer simulation and by comparison between static and dynamic control method, it proves that the latter one is more adaptive to the changes of casting speed, which leads to lower fluctuation of surface temperature.     

The Numerical Simulation Commercial Software for Secondary Cooling Process in Billet Continuous Casting

A numerical simulation commercial software has been developed by the object-oriented Visual Basic programming language on the basis of the 2D mathematical model of secondary cooling Process in billet continuous casting. Thereby an effective experimenting tool for computer simulation of continuous casting process is gained. By simulation with the software, the caster structures and operating parameters in continuous casting can be designed and optimized. The simulating calculation examples on several casters and its production applications indicate that the commercial software developed has more accuracy, practicability and commonality, as also as simpler operating capability. The simulated results have been successfully applied to the design and production of the high-efficiency modification for several billet casters interiorly.     

Driver Model of Steering Direction Control for Automobiles

Creating a suitable driver model is one of the most important parts in the closed-loop system of driver-vehicle-road.Several kinds of driver models have been created based on the traditional control theories such as transfer function,optimization control and the compensation control.But owing to the driver's characteristics of nonlinear and time-variable,it's difficult for those proposed driver models to mimic drivers' action.While accounting for the inherent manual control characteristics and limitations of the mankind,the intelligent control methods have been applied in creating driver models based on the fuzzy control,neural networks control and fuzzy-neural networks control theory.     

Predictive Control Approach for Active Power Filter Based on Neural Networks

In this paper, a predictive control approach using neural networks for active power filter is proposed. The control system of active power filter using this method make using of the internal model control technology based on neural networks, meanwhile, to solve its questions such as lag because of calculating using neural networks, a predictive model based on neural networks is introduced. Simulation analysis shows that this control approach can compensate the lag of system and take advantage of self-adaptive characteristic of neural networks. Good result can be obtained.     

The Mathematical Model of Cooling and Heat Transfer for the Solidification of Thin Slab during Continuous Casting Process

In the established model, the cooling differences are considered between the surface of inner radius and that of outer radius, and in the transverse direction of thin slab. And the conception for the effective coefficient of spraying water in continuous casting is firstly put forward. According to different casting speeds and different cooling zones, different time step lengths are adopted. In this model the heat transfer differences are thought over among vertical and curved zones, wide and narrow surfaces an well as angular zone of mould. The method of the corrected equivalent specific heat is used to deal with latent heat. The influence of forced convection is considered on heat transfer. Therefore, the model has higher accuracy and is consistent with the practice.     

A Kind of Fuzzy System Modelling and Control Based on Neural Networks

Combining artificial neural networks(ANN) with fuzzy system theory,a kind of modelling & control method of fuzzy system based on ANN is presented.The simulation researches have verified that the proposed approach can be applied effectively to a number of control systems which are defficult to build strict mathematical model.     

PID Control for Multivariable System Based on Ameliorative RBF Neural Networks

Aiming at systems which are of characteristics of multi-input and multi-output, nonlinearity and time-variation in the industrial control fields, this paper presents a intelligent PID control method based on ameliorative RBF neural networks, which constructs RBF neural networks identifier on-line and identifies a controlled object on-line by means of adopting the nearest neighbor-clustering algorithm, and adjusts parameters of PID controller on-line and realizes decoupiing control of multivariable, nonlinear and time-variation system. The simulation result indicates that the controller can get parameters which are optimal under some control law, it makes the decoupled system, compared to the PID control method based on the conventional RBF neural networks, has perfect dynamic and static performances, possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.     

Application of BP Neural Networks in Inventory Dynamic Modeling

The authors establish an original inventory model based on BP neural networks in dynamic environment using the inventory history data, and overcome the net overfitting problem occurred with insufficient samples by using early stopping method. After a simple-relation inventory model training is attained, they get inventory model and analyze it dynamically by reconstructing the model after getting new sample data. An example is provided to illustrate the model. The theoretical evidence is provided for the inventory system to make management decision.     

Two-dimension Thermal Elasto-plastic and Creep Stress Model for Thin Slab Strand in Continous Casting

The thin-slab continuous casting is an important new technology in the world. The major key of this technology is to assure the good quality and the less crack of thin slab. Thus in this paper a two-dimension thermal elasto-plastic and creep stress (TEPC) model for thin slab strand is developed. The equations between stress and strain are given on thermal creep condition for elastic area, plastic area and the transitional area of thin-slab strand section.The formula of equivalent plasto-strain increment is obtained. The boundary conditions of the model given is fairly accurate. Therefore, the TEPC model is possessed of higher precision, and the model is also used to analyze the stress and strain distribution of strand in continuous casting.     

Control model for secondary cooling of continuous casting based on compensation temperature of the difference between liquidus and solidus

During continuous casting process, the composition of molten steel often varies with different heats, which leads to the big fluctuation of billet surface temperature when the traditional parameter water control model is applied to control the process. Additionally, it is difficult to keep the temperature at the straightening point of the billet within a reasonable range. Given above consideration, a new control model for secondary cooling of continuous casting based on compensation temperature of the difference between liquidus and solidus has been presented. Meanwhile, the temperature field of the billet is simulated with both the parameter water control model and the new secondary cooling control model, and the results indicate that the new control model for secondary cooling of continuous casting could perform better when it is used to control the surface temperature at straightening points of billet, thereby ensuring the quality of the billet.     

Computational Simulation on Temperature Field of Slab Continuous Casting Mold

On the core concepts that the distributing of temperature and solidified slab shell in mold are a stable process, a new method to calculate the temperature field in mold has been promoted. Consequently, a coupling model on fluid filed and temperature field in stable state has also been established. The concept of effective heat capacity is introduced to deal with the latent heat source term from phase transformation. During the programming for computation, the dynamic updating method is also applied to simulate the influence of solidification on physical properties. The resolution results of this model are analyzed and compared with the tested thickness of solidified shell from casting broke out slab, which demonstrates the correctness and applicability of this model to the practical continuous casting process. Additionally, the thickness distribution of solidified shell in slab mold are also studied in detail.     

Network Partitioning Based on Threshold Search and Dynamic Scatter for Voltage/Var Control

Secondary Voltage Control is a new way of voltage control,firstly the power system is divided into many control areas whose electric distance is remote.The partitioning method of secondary voltage control is studied and an algorithm that combination of the threshold search and dynamic scatter is presented.That is,the initial grouping scheme is obtained by searching the threshold value.The dynamic scatter method then is used to regulate and improve the initial results.The method is based on system's physical character,it's unnecessary to modify the network's model and analysis the eigenvalue,so the compute rate is fast.Through comparing the method and the traditional methods,this method is proved to be a reasonable and feasible partitioning scheme.     

Mathematical Model of Control Cooling for Screw Rod After Rolling

The on line hot treatment can not only boost the strength but also gain lower cost. It is usually called tempcore which was developed greatly these years. The process of tempcor art is introduced and the core subject mathematical models is studied. According to the heating exchanging property of screw rod in cooling after rolling.Two mathematical models including beginning cooling model and cooling water amount model are obtained by analysing, deducing theoretically and simplifying mathematically. Its structure is simple and practiced .The parameter of model is obtained from measuring data of work site. It is able to suite the change of work site, so it can be used in practiced controlling.     

Pre-bid Decision-making Process Based on Artificial Neural Networks Technology

There are complicated non-linear relations among influence factors, and between influence factors and decision - making results, which cannot be handled by common analytical method effectively. So the ANN technology was applied in the pre-bid decision-making processes. An indicator system of influence factors for pre-bid decision-making process was built based on extensive investigations, comparisons and analyses, with due considerations to the ANN analysis requirements. And then the criterion and method for quantifying the indicators were put forward by quantificational methods and fuzzy theories. An ANN model for pre-bid decision- making process was constructed and performed in Matlab, which has powerful learning ability and fast learning speed. The model was verified by a few examples from engineering practice.     

Qualitative Analysis of an Exponential Dynamic Neural Networks

The exponential dynamic neural network proposed.by T.D.Chiuch and R.M.Goodman in 1988 is investigated. A concise sufficient condition for the given standard patterns to bestable is presented. A one-step conversence radius of such a stable state is obtained. It is also shownthat there do not exist sporious stable states in the probabilistic sense.     

The Application of Fuzzy Neural Networks for Power Transformer Fault Diagnosis

This paper presents the application of fuzzy neural networks (FNN) in power transformer faults diagnosis.A FNN model is builded,in which input is transformer oil color spectrum analysis and output is fault type.The test results of fault examples show its effectiveness and potential applicable worthiness.     

Applications of the Fuzzy Neural Networks to Short term Load Forecasting

This paper presents a fuzzy neural network approach to short term load forecasting.It can predict the hourly loads for next day or next week with the fuzzy information.The practical examples have proved the efficiencies of the proposed approach.