This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary,and established four kinds of technological process control models of reverse logistics i...This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary,and established four kinds of technological process control models of reverse logistics in manufacturing system according to different processing methods. These models embed each other that form a cubic control system of reverse logistics.展开更多
A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and ...A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.展开更多
An integrated metallurgical model was developed to predict microstructure evolution and mechanical properties of low-carbon steel plates produced by TMCP. The metallurgical phenomena occurring during TMCP and mechanic...An integrated metallurgical model was developed to predict microstructure evolution and mechanical properties of low-carbon steel plates produced by TMCP. The metallurgical phenomena occurring during TMCP and mechanical properties were predicted for different process parameters. In the later passes full recrystallization becomes difficult to occur and higher residual strain remains in austenite after rolling. For the reasonable temperature and cooling schedule, yield strength of 30 mm plain carbon steel plate can reach 310 MPa. The first on-line application of prediction and control of microstructure and properties (PCMP) in the medium plate production was achieved. The predictions of the system are in good agreement with measurements.展开更多
Modeling and attitude control methods for a satellite with a large deployable antenna are studied in the present paper. Firstly, for reducing the model dimension, three dynamic models for the deploying process are dev...Modeling and attitude control methods for a satellite with a large deployable antenna are studied in the present paper. Firstly, for reducing the model dimension, three dynamic models for the deploying process are developed, which are built with the methods of multi-rigid-body dynam- ics, hybrid coordinate and substructure. Then an attitude control method suitable for the deploying process is proposed, which can keep stability under any dynamical parameter variation. Subse- quently, this attitude control is optimized to minimize attitude disturbance during the deploying process. The simulation results show that this attitude control method can keep stability and main- tain proper attitude variation during the deploying process, which indicates that this attitude con- trol method is suitable for practical applications.展开更多
This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network,...This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.展开更多
Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves ...Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to accommodate nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC). It also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design, which relieves practising engineers from the need for deriving a physical-principles based model first. An on-line realisation technique for implementing NMPC is then developed and applied to a Mitsubishi Chemicals polymerisation reaction process. Results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the developed approach lie not only in control performance superior to existing NMPC methods, but also in eliminating the need for converting an analytical model and then convert it to a Volterra model obtainable only up to the second order. Keywords Model predictive control - Volterra series - process control - nonlinear control Yun Li is a senior lecturer at University of Glasgow, UK, where has taught and researched in evolutionary computation and control engineering since 1991. He worked in the UK National Engineering Laboratory and Industrial Systems and Control Ltd, Glasgow in 1989 and 1990. In 1998, he established the IEEE CACSD Evolutionary Computation Working Group and the European Network of Excellence in Evolutionary Computing (EvoNet) Workgroup on Systems, Control, and Drives. In summer 2002, he served as a visiting professor to Kumamoto University, Japan. He is also a visiting professor at University of Electronic Science and Technology of China. His research interests are in parallel processing, design automation and discovery of engineering systems using evolutionary learning and intelligent search techniques. Applications include control, system modelling and prediction, circuit design, microwave engineering, and operations management. He has advised 12 Ph.D.s in evolutionary computation and has 140 publications.Hiroshi Kashiwagi received B.E, M.E. and Ph.D. degrees in measurement and control engineering from the University of Tokyo, Japan, in 1962, 1964 and 1967 respectively. In 1967 he became an Associate Professor and in 1976 a Professor at Kumamoto University. From 1973 to 1974, he served as a visiting Associate Professor at Purdue University, Indiana, USA. From 1990 to 1994, he was the Director at Computer Center of Kumamoto University. He has also served as a member of Board of Trustees of Society of Instrument and Control Engineers (SICE), Japan, Chairman of Kyushu Branch of SICE and General Chair of many international conferences held in Japan, Korea, Chin and India. In 1994, he was awarded SICE Fellow for his contributions to the field of measurement and control engineering through his various academic activities. He also received the Gold Medal Prize at ICAUTO’95 held in India. In 1997, he received the “Best Book Award” from SICE for his new book entitled “M-sequence and its application” written in Japanese and published in 1996 by Shoukoudou Publishing Co. in Japan. In 1999, he received the “Best Paper Award” from SICE for his paper “M-transform and its application to system identification”. His research interests include signal processing and applications, especially pseudorandom sequence and its applications to measurement and control engineering.展开更多
This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected ...This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.展开更多
For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control mac...For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control machining error, the method of integrating multivariate statistical process control （MSPC） and stream of variations （SoV） is proposed. Firstly, machining error is modeled by multi-operation approaches for part machining process. SoV is adopted to establish the mathematic model of the relationship between the error of upstream operations and the error of downstream operations. Here error sources not only include the influence of upstream operations but also include many of other error sources. The standard model and the predicted model about SoV are built respectively by whether the operation is done or not to satisfy different requests during part machining process. Secondly, the method of one-step ahead forecast error （OSFE） is used to eliminate autocorrelativity of the sample data from the SoV model, and the T2 control chart in MSPC is built to realize machining error detection according to the data characteristics of the above error model, which can judge whether the operation is out of control or not. If it is, then feedback is sent to the operations. The error model is modified by adjusting the operation out of control, and continually it is used to monitor operations. Finally, a machining instance containing two operations demonstrates the effectiveness of the machining error control method presented in this paper.展开更多
The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously ...The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously developed tools,including the norm-bounding technique for relaxing the disturbance-related constraint handling,the dynamic output feedback law,the notion of quadratic boundedness for specifying the closed-loop stability,and the ellipsoidal state estimation error bound for guaranteeing the recursive feasibility,are merged in the control design.Some previous approaches are shown to be the special cases.An example of continuous stirred tank reactor(CSTR) is given to show the effectiveness of the proposed approaches.展开更多
With the development of advanced high strength steel,especially for dual-phase steel,the model algorithm for cooling control after hot rolling has to achieve the targeted coiling temperature control at the location of...With the development of advanced high strength steel,especially for dual-phase steel,the model algorithm for cooling control after hot rolling has to achieve the targeted coiling temperature control at the location of downcoiler whilst maintaining the cooling path control based on strip microstructure along the whole cooling section.A cooling path control algorithm was proposed for the laminar cooling process as a solution to practical difficulties associated with the realization of the thermal cycle during cooling process.The heat conduction equation coupled with the carbon diffusion equation with moving boundary was employed in order to simulate temperature change and phase transformation kinetics,making it possible to observe the temperature field and the phase fraction of the strip in real time.On this basis,an optimization method was utilized for valve settings to ensure the minimum deviations between the predicted and actual cooling path of the strip,taking into account the constraints of the cooling equipment′s specific capacity,cooling line length,etc.Results showed that the model algorithm was able to achieve the online cooling path control for dual-phase steel.展开更多
In this paper,we present a review of the current literature on distributed(or partially decentralized) control of chemical process networks.In particular,we focus on recent developments in distributed model predictive...In this paper,we present a review of the current literature on distributed(or partially decentralized) control of chemical process networks.In particular,we focus on recent developments in distributed model predictive control,in the context of the specific challenges faced in the control of chemical process networks.The paper is concluded with some open problems and some possible future research directions in the area.展开更多
Control of sludge age and mixed liquid suspended solids concentration in the activated sludge process is critical for ensuring effective wastewater treatment. A nonlinear dynamic model for a step-feed activated sludge...Control of sludge age and mixed liquid suspended solids concentration in the activated sludge process is critical for ensuring effective wastewater treatment. A nonlinear dynamic model for a step-feed activated sludge process was developed in this study. The system is based on the control of the sludge age and mixed liquor suspended solids in the aerator of last stage by adjusting the sludge recycle and wastage flow rates respectively. The simulation results showed that the sludge age remained nearly constant at a value of 16 d in the variation of the influent characteristics. The mixed liquor suspended solids in the aerator of last stage were also maintained to a desired value of 2500 g/m3 by adjusting wastage flow rates.展开更多
With regards to the assembly line of cost control of Dechang(HK)company,the motor housing’s cost control of process will be necessarily respected.Because the supply quantity is big in a machine the price of motor hou...With regards to the assembly line of cost control of Dechang(HK)company,the motor housing’s cost control of process will be necessarily respected.Because the supply quantity is big in a machine the price of motor housing is small,so that the cost control of automatic production line is significant with modeling.It is found that the control of equipment includes in shaft and crank linkage for benefit which also needs to be controlled in detail.For the sake of benefits can we fundamentally resolve the main problem of high cost process.展开更多
This paper provides a mathematical model for the billet reheating process in furnace.A new optimum method is brought up that the objective function is the integral value of enthalpy increasing process of a billet.Diff...This paper provides a mathematical model for the billet reheating process in furnace.A new optimum method is brought up that the objective function is the integral value of enthalpy increasing process of a billet.Different delays are simulated and calculated,some proper delay strategies are ob- tained.The on-line computer control model is de- veloped.The real production conditions simulated, the temperature deviation of drop out billet from the target temperature is kept within±15℃.展开更多
There are lots of physical changes and chemical reactions in the processes of iron and steel making, these processes are quite complex in the aspect of heat transfer.The processes of iron and steel making can be appro...There are lots of physical changes and chemical reactions in the processes of iron and steel making, these processes are quite complex in the aspect of heat transfer.The processes of iron and steel making can be approximately divided into three kinds.The first kinds are the processes of fusion metallurgy which involve enormous chemical reactions,such as blast furnace,converter,electric furnace and coke oven.The second kinds are the processes of heating and cooling which are mainly the physical changes,such as walking-beam reheating furnace,annular heating furnace and car-type furnace.The third kinds are the processes of heat treatment which mainly adjust metallurgical structure of metal,such as roller hearth heat treatment furnace, strip continuous heat treatment vertical/horizontal furnace and HPH bell-type annealing furnace.Every process can only be finished in particular thermal equipment.And all the physical and chemical processes mentioned above must obey first principles of engineering thermodynamics,heat & mass transfer,hydromechanics, combustion,metallurgy physical chemistry etc,and which can be summarized as principle of heat transfer,mass transfer,momentum transfer and chemistry reaction.In this paper,based on first principle of heat and mass transfer in iron and steel making processes,a series of mathematical models of thermal equipments and processes are presented.Such as the model of hot-blast stoves,coke oven,CDQ-boiler system,sintering, reheating furnace,soaking furnace,annular heating furnace,roller hearth heat treatment furnace,strip continuous heat treatment vertical/horizontal furnace,HPH bell-type annealing furnace,control cooling of medium plate,burner,heat exchanger and regenerative burner etc.The on-line application of the model is based on experimental certification of the mathematical model.And finally the computer optimization system of metallurgical thermal process is obtained.展开更多
Thick metal plate rolling process has become more and more important in building a flat roof of drilling on the bottom at sea. This is because not only the product quality requirement higher and higher but also the ma...Thick metal plate rolling process has become more and more important in building a flat roof of drilling on the bottom at sea. This is because not only the product quality requirement higher and higher but also the marketing competition. To improve the process of thick metal plate rolling and to increase productivity a numerical controlled rolling process is developed, which include the process planning, the mathematical model establishment and the numerical control system development. The process is for the 17 000 kN×3 000 mm movable up roller bending machine. According to the machine configuration non-symmetry rolling process is planed. This makes it possible to integrate all the steps of plate shaping up such as end side bending, several times of semi-shape bending and the last shape finishing. Since the process will perform under the numerical controlled condition whole steps of the process are considered can be worked in the automatic cycle. The mathematic model consists of two sections, the theory model and the experience parameters model. Which takes the original plate parameters such as geometry and mechanics, characters of the machine such as the movement limits, tonnage and so on as input and calculates all the parameters needed in process performing. Meanwhile, the mathematic Model is totally adapted to the control system. The numerical control system development scheme is based on all the works above. Here, a system plan is provided. The functional modules and hardware selection, in detail, are introduced. The system software on top level and the controlling software for controller are developed. And some unit techniques in the system such as timer setting, communication between system and controller, video integration, and the ability of resisting impact force are introduced. The process has been used successfully in production for more than two years. Practice approves that the process is robust.展开更多
The most important parameters which control the electrolytic process are the concentrations of zinc and sulfuric acid in the electrolyte. An expert control strategy for determining and tracking the optimal concentrati...The most important parameters which control the electrolytic process are the concentrations of zinc and sulfuric acid in the electrolyte. An expert control strategy for determining and tracking the optimal concentrations was proposed, which uses neural networks, rule models and a single loop control scheme. First, the process was described and the strategy that features an expert controller and three single loop controllers was explained. Next, neural networks and rule models were constructed based on statistical data and empirical knowledge on the process. Then, the expert controller for determining the optimal concentrations was designed through a combination of the neural networks and rule models. The three single loop controllers used the PI algorithm to track the optimal concentrations. Finally, the implementation of the proposed strategy were presented. The run results show that the strategy provides not only high purity metallic zinc, but also significant economic benefits.展开更多
Of the two methods of getting the mathematical model of a given system,modeling and i-dentification,the first is of the advantage of“knowing it in the detailed inside”.In this paper,after the common technological pr...Of the two methods of getting the mathematical model of a given system,modeling and i-dentification,the first is of the advantage of“knowing it in the detailed inside”.In this paper,after the common technological process of paper making is approached,a simplified physicalimitation and the mathematical model are presented.The resulted model by means of modelingis of the same form with that through,identification by K.J.Astrom in 1970.The course ofmodel deriving is described in detail,from which one can see clearly how the minor factors ofthe dynamics are omitted and what may be included in the unmodeled dynamics.At the sametime,the limit to its usage is also given.展开更多
文摘This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary,and established four kinds of technological process control models of reverse logistics in manufacturing system according to different processing methods. These models embed each other that form a cubic control system of reverse logistics.
基金Item Sponsored by National Natural Science Foundation of China(50074026)
文摘A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.
基金This work was financially supported by the High Technology Development Program(No.2001AA339030)the National Natural Science Foundation of China(No.50334010).
文摘An integrated metallurgical model was developed to predict microstructure evolution and mechanical properties of low-carbon steel plates produced by TMCP. The metallurgical phenomena occurring during TMCP and mechanical properties were predicted for different process parameters. In the later passes full recrystallization becomes difficult to occur and higher residual strain remains in austenite after rolling. For the reasonable temperature and cooling schedule, yield strength of 30 mm plain carbon steel plate can reach 310 MPa. The first on-line application of prediction and control of microstructure and properties (PCMP) in the medium plate production was achieved. The predictions of the system are in good agreement with measurements.
基金sponsored by the National Natural Science Foundation of China (No. 11272172)
文摘Modeling and attitude control methods for a satellite with a large deployable antenna are studied in the present paper. Firstly, for reducing the model dimension, three dynamic models for the deploying process are developed, which are built with the methods of multi-rigid-body dynam- ics, hybrid coordinate and substructure. Then an attitude control method suitable for the deploying process is proposed, which can keep stability under any dynamical parameter variation. Subse- quently, this attitude control is optimized to minimize attitude disturbance during the deploying process. The simulation results show that this attitude control method can keep stability and main- tain proper attitude variation during the deploying process, which indicates that this attitude con- trol method is suitable for practical applications.
基金Supported by UK EPSRC (grants GR/N13319 and GR/R 10875)
文摘This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.
文摘Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to accommodate nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC). It also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design, which relieves practising engineers from the need for deriving a physical-principles based model first. An on-line realisation technique for implementing NMPC is then developed and applied to a Mitsubishi Chemicals polymerisation reaction process. Results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the developed approach lie not only in control performance superior to existing NMPC methods, but also in eliminating the need for converting an analytical model and then convert it to a Volterra model obtainable only up to the second order. Keywords Model predictive control - Volterra series - process control - nonlinear control Yun Li is a senior lecturer at University of Glasgow, UK, where has taught and researched in evolutionary computation and control engineering since 1991. He worked in the UK National Engineering Laboratory and Industrial Systems and Control Ltd, Glasgow in 1989 and 1990. In 1998, he established the IEEE CACSD Evolutionary Computation Working Group and the European Network of Excellence in Evolutionary Computing (EvoNet) Workgroup on Systems, Control, and Drives. In summer 2002, he served as a visiting professor to Kumamoto University, Japan. He is also a visiting professor at University of Electronic Science and Technology of China. His research interests are in parallel processing, design automation and discovery of engineering systems using evolutionary learning and intelligent search techniques. Applications include control, system modelling and prediction, circuit design, microwave engineering, and operations management. He has advised 12 Ph.D.s in evolutionary computation and has 140 publications.Hiroshi Kashiwagi received B.E, M.E. and Ph.D. degrees in measurement and control engineering from the University of Tokyo, Japan, in 1962, 1964 and 1967 respectively. In 1967 he became an Associate Professor and in 1976 a Professor at Kumamoto University. From 1973 to 1974, he served as a visiting Associate Professor at Purdue University, Indiana, USA. From 1990 to 1994, he was the Director at Computer Center of Kumamoto University. He has also served as a member of Board of Trustees of Society of Instrument and Control Engineers (SICE), Japan, Chairman of Kyushu Branch of SICE and General Chair of many international conferences held in Japan, Korea, Chin and India. In 1994, he was awarded SICE Fellow for his contributions to the field of measurement and control engineering through his various academic activities. He also received the Gold Medal Prize at ICAUTO’95 held in India. In 1997, he received the “Best Book Award” from SICE for his new book entitled “M-sequence and its application” written in Japanese and published in 1996 by Shoukoudou Publishing Co. in Japan. In 1999, he received the “Best Paper Award” from SICE for his paper “M-transform and its application to system identification”. His research interests include signal processing and applications, especially pseudorandom sequence and its applications to measurement and control engineering.
文摘This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.
基金National Natural Science Foundation of China (70931004)
文摘For aircraft manufacturing industries, the analyses and prediction of part machining error during machining process are very important to control and improve part machining quality. In order to effectively control machining error, the method of integrating multivariate statistical process control （MSPC） and stream of variations （SoV） is proposed. Firstly, machining error is modeled by multi-operation approaches for part machining process. SoV is adopted to establish the mathematic model of the relationship between the error of upstream operations and the error of downstream operations. Here error sources not only include the influence of upstream operations but also include many of other error sources. The standard model and the predicted model about SoV are built respectively by whether the operation is done or not to satisfy different requests during part machining process. Secondly, the method of one-step ahead forecast error （OSFE） is used to eliminate autocorrelativity of the sample data from the SoV model, and the T2 control chart in MSPC is built to realize machining error detection according to the data characteristics of the above error model, which can judge whether the operation is out of control or not. If it is, then feedback is sent to the operations. The error model is modified by adjusting the operation out of control, and continually it is used to monitor operations. Finally, a machining instance containing two operations demonstrates the effectiveness of the machining error control method presented in this paper.
基金Supported by the National High Technology Research and Development Program of China(2014AA041802)the National Natural Science Foundation of China(61573269)
文摘The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously developed tools,including the norm-bounding technique for relaxing the disturbance-related constraint handling,the dynamic output feedback law,the notion of quadratic boundedness for specifying the closed-loop stability,and the ellipsoidal state estimation error bound for guaranteeing the recursive feasibility,are merged in the control design.Some previous approaches are shown to be the special cases.An example of continuous stirred tank reactor(CSTR) is given to show the effectiveness of the proposed approaches.
文摘With the development of advanced high strength steel,especially for dual-phase steel,the model algorithm for cooling control after hot rolling has to achieve the targeted coiling temperature control at the location of downcoiler whilst maintaining the cooling path control based on strip microstructure along the whole cooling section.A cooling path control algorithm was proposed for the laminar cooling process as a solution to practical difficulties associated with the realization of the thermal cycle during cooling process.The heat conduction equation coupled with the carbon diffusion equation with moving boundary was employed in order to simulate temperature change and phase transformation kinetics,making it possible to observe the temperature field and the phase fraction of the strip in real time.On this basis,an optimization method was utilized for valve settings to ensure the minimum deviations between the predicted and actual cooling path of the strip,taking into account the constraints of the cooling equipment′s specific capacity,cooling line length,etc.Results showed that the model algorithm was able to achieve the online cooling path control for dual-phase steel.
基金supported by Australian Research Council(ARC)Discovery Project(No.DP130103330)
文摘In this paper,we present a review of the current literature on distributed(or partially decentralized) control of chemical process networks.In particular,we focus on recent developments in distributed model predictive control,in the context of the specific challenges faced in the control of chemical process networks.The paper is concluded with some open problems and some possible future research directions in the area.
基金The National Hi Tech Development Program (863) of China(No.2003AA601110) and the National Natural Science Foundation Key Item of China(No.50138010)
文摘Control of sludge age and mixed liquid suspended solids concentration in the activated sludge process is critical for ensuring effective wastewater treatment. A nonlinear dynamic model for a step-feed activated sludge process was developed in this study. The system is based on the control of the sludge age and mixed liquor suspended solids in the aerator of last stage by adjusting the sludge recycle and wastage flow rates respectively. The simulation results showed that the sludge age remained nearly constant at a value of 16 d in the variation of the influent characteristics. The mixed liquor suspended solids in the aerator of last stage were also maintained to a desired value of 2500 g/m3 by adjusting wastage flow rates.
文摘With regards to the assembly line of cost control of Dechang(HK)company,the motor housing’s cost control of process will be necessarily respected.Because the supply quantity is big in a machine the price of motor housing is small,so that the cost control of automatic production line is significant with modeling.It is found that the control of equipment includes in shaft and crank linkage for benefit which also needs to be controlled in detail.For the sake of benefits can we fundamentally resolve the main problem of high cost process.
文摘This paper provides a mathematical model for the billet reheating process in furnace.A new optimum method is brought up that the objective function is the integral value of enthalpy increasing process of a billet.Different delays are simulated and calculated,some proper delay strategies are ob- tained.The on-line computer control model is de- veloped.The real production conditions simulated, the temperature deviation of drop out billet from the target temperature is kept within±15℃.
文摘There are lots of physical changes and chemical reactions in the processes of iron and steel making, these processes are quite complex in the aspect of heat transfer.The processes of iron and steel making can be approximately divided into three kinds.The first kinds are the processes of fusion metallurgy which involve enormous chemical reactions,such as blast furnace,converter,electric furnace and coke oven.The second kinds are the processes of heating and cooling which are mainly the physical changes,such as walking-beam reheating furnace,annular heating furnace and car-type furnace.The third kinds are the processes of heat treatment which mainly adjust metallurgical structure of metal,such as roller hearth heat treatment furnace, strip continuous heat treatment vertical/horizontal furnace and HPH bell-type annealing furnace.Every process can only be finished in particular thermal equipment.And all the physical and chemical processes mentioned above must obey first principles of engineering thermodynamics,heat & mass transfer,hydromechanics, combustion,metallurgy physical chemistry etc,and which can be summarized as principle of heat transfer,mass transfer,momentum transfer and chemistry reaction.In this paper,based on first principle of heat and mass transfer in iron and steel making processes,a series of mathematical models of thermal equipments and processes are presented.Such as the model of hot-blast stoves,coke oven,CDQ-boiler system,sintering, reheating furnace,soaking furnace,annular heating furnace,roller hearth heat treatment furnace,strip continuous heat treatment vertical/horizontal furnace,HPH bell-type annealing furnace,control cooling of medium plate,burner,heat exchanger and regenerative burner etc.The on-line application of the model is based on experimental certification of the mathematical model.And finally the computer optimization system of metallurgical thermal process is obtained.
文摘Thick metal plate rolling process has become more and more important in building a flat roof of drilling on the bottom at sea. This is because not only the product quality requirement higher and higher but also the marketing competition. To improve the process of thick metal plate rolling and to increase productivity a numerical controlled rolling process is developed, which include the process planning, the mathematical model establishment and the numerical control system development. The process is for the 17 000 kN×3 000 mm movable up roller bending machine. According to the machine configuration non-symmetry rolling process is planed. This makes it possible to integrate all the steps of plate shaping up such as end side bending, several times of semi-shape bending and the last shape finishing. Since the process will perform under the numerical controlled condition whole steps of the process are considered can be worked in the automatic cycle. The mathematic model consists of two sections, the theory model and the experience parameters model. Which takes the original plate parameters such as geometry and mechanics, characters of the machine such as the movement limits, tonnage and so on as input and calculates all the parameters needed in process performing. Meanwhile, the mathematic Model is totally adapted to the control system. The numerical control system development scheme is based on all the works above. Here, a system plan is provided. The functional modules and hardware selection, in detail, are introduced. The system software on top level and the controlling software for controller are developed. And some unit techniques in the system such as timer setting, communication between system and controller, video integration, and the ability of resisting impact force are introduced. The process has been used successfully in production for more than two years. Practice approves that the process is robust.
文摘The most important parameters which control the electrolytic process are the concentrations of zinc and sulfuric acid in the electrolyte. An expert control strategy for determining and tracking the optimal concentrations was proposed, which uses neural networks, rule models and a single loop control scheme. First, the process was described and the strategy that features an expert controller and three single loop controllers was explained. Next, neural networks and rule models were constructed based on statistical data and empirical knowledge on the process. Then, the expert controller for determining the optimal concentrations was designed through a combination of the neural networks and rule models. The three single loop controllers used the PI algorithm to track the optimal concentrations. Finally, the implementation of the proposed strategy were presented. The run results show that the strategy provides not only high purity metallic zinc, but also significant economic benefits.
文摘Of the two methods of getting the mathematical model of a given system,modeling and i-dentification,the first is of the advantage of“knowing it in the detailed inside”.In this paper,after the common technological process of paper making is approached,a simplified physicalimitation and the mathematical model are presented.The resulted model by means of modelingis of the same form with that through,identification by K.J.Astrom in 1970.The course ofmodel deriving is described in detail,from which one can see clearly how the minor factors ofthe dynamics are omitted and what may be included in the unmodeled dynamics.At the sametime,the limit to its usage is also given.
