Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–...Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.展开更多
During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control...During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control in sintering production to keep the mass concentration of NO_(x)in sintering flue gas at a low level.Through industrial trials at sintering sites,methods such as correlation analysis,path analysis,and multiple linear regression were applied to analyze the influence of various factors on NO emissions during the sintering process.The results indicate that negative correlations exist between nitrogen monoxide(NO)emissions and negative pressure,permeability index,O_(2) concentration,CO concentration,and flue gas temperature.Conversely,positive correlations exist between NO emissions and dust concentration,water vapor volume fraction,and sintering bed speed.Among these factors,O_(2) concentration and dust concentration are identified as the most significant influencing factors on NO emissions.By analyzing the masses and modes of influence of different factors,the mechanisms of action of each factor were obtained.Specifically,O_(2) concentration,dust concentration,permeability index,CO concentration,and flue gas temperature play a direct dominant role in NO emissions during the sintering process,while water vapor volume fraction,sintering trolley speed,and negative pressure have an indirect effect.A predictive model for NO mass concentration in flue gas was established with an accuracy rate of 91.6%,showing consistent overall trends with actual values.Finally,denitrification strategies for sintering industrial production were proposed,along with prospects for preliminary denitrification of sintering flue gas using fluidized bed conditions in the duct.展开更多
L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled pro...L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.展开更多
Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and proces...Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.展开更多
Grain size control of tungsten powder is essential for high quality tungsten products. Based on studies on the hydrogen reduction process of tungsten oxide, a microcomputer system is described for reduction process co...Grain size control of tungsten powder is essential for high quality tungsten products. Based on studies on the hydrogen reduction process of tungsten oxide, a microcomputer system is described for reduction process control. The system, now running in Zhuzhou Tungsten and Molybdenum Materials Plant, controls the temperature of the reduction furnace and hydrogen pressure. It also controls a mechanical pusher which pushs the boats charged with blue tungsten oxide into the furnace tubes. Some of the technical problems in the process are analysed.展开更多
A mathematical model of the decarburization reaction zone was established for the Ruhrstahl–Heraeus (RH) forced oxygen blowing decarburization process by Matlab R2022b software. For the problem of inaccurate predicti...A mathematical model of the decarburization reaction zone was established for the Ruhrstahl–Heraeus (RH) forced oxygen blowing decarburization process by Matlab R2022b software. For the problem of inaccurate prediction due to the large variation range of oxygen absorption rate under different process conditions, we statistically analyzed the main factors affecting the oxygen absorption rate. The backpropagation neural network was used to train and predict the oxygen absorption rate and was used to calculate the RH decarburization reaction zone model. We designed and developed a mathematical modeling software with process control of decarburization in RH degasser, which can realize the change of operating process parameters in the dynamic prediction process. The optimized mathematical model has more than 95% of the furnaces whose absolute error in calculation of carbon content is within ± 5 × 10^(−6), more than 90% of the heats whose relative error in calculation of oxygen content is within ± 15%, and the average absolute error of calculation of oxygen content is 26.4 × 10^(−6). Finally, we studied the influence of oxygen blowing timing, oxygen blowing volume and initial oxygen content on the forced decarburization process.展开更多
The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and...The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process展开更多
A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solvin...A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.展开更多
The methylotrophic yeast Pichia pastoris is a highly successful system for production of a variety of heterologous proteins due to its unique features/abilities for effective protein expression, and tremendous efforts...The methylotrophic yeast Pichia pastoris is a highly successful system for production of a variety of heterologous proteins due to its unique features/abilities for effective protein expression, and tremendous efforts have been made to increase heterologous protein productivity by P. pastoris in recent years. When new engineered yeast strains are constructed and are ready to use tot industrial protein production, process control and optimization techniques should be applied to improve the fermentation performance in the following aspects： （1） increase recombinant cell concentrations in fermentor to high density during growth phase; （2） effectively induce heterologous proteins by enhancing/stabilizing titers or concentrations of the proteins during induction phase; （3） decrease operation costs by relieving the working loads of heat-exchange and oxygen supply. This article reviews and discusses the key and commonly used techniques in heterologous protein production by P. pastoris, with the focus on optimizations of fermentation media and basic operation conditions, development of optimal glycerol feeding strategies for achieving high density cultivation of P. pastoris and effective heterologous protein induction methods by regulating specific growth rate, methanol concentration, temperatures, mixture ratio of multi-carbon substrates, etc. Metabolic analysis for recombinant protein production by P. pastoris is also introduced to interpret the mechanism of sub-optimal heterologous protein production and to explore further optimal expression methods.展开更多
For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique du...For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.展开更多
Different amounts of absolute ethanol(0-50 mL)are used as process control agents(PCA)to prepare FeCoNiAlCr0.9 high entropy alloy(HEA)powders via 90 h ball milling.The results show that the increased amount of PCA play...Different amounts of absolute ethanol(0-50 mL)are used as process control agents(PCA)to prepare FeCoNiAlCr0.9 high entropy alloy(HEA)powders via 90 h ball milling.The results show that the increased amount of PCA plays an active role in the crystallinity of powders,and regulate the thickness and size distribution of flake particles.As the volume of PCA increases,the real and imaginary parts(ε′andε″)of complex permittivity get increased by the enhancement of the interface polarization and surface polarization,while the increase in the real and imaginary parts(μ′andμ″)of complex permeability arises from the increased anisotropic energy.The addition of PCA not only promotes the reflection loss but also extends the effective bandwidth(up to 4.28 GHz).Here,the performance adjustment of HEA electromagnetic absorber is realized by forthrightly changing the process parameters of ball milling.展开更多
Process control is an effective approach to reduce the NO_(x) emission from sintering flue gas.The effects of different materials adhered on coke breeze on NO_(x) emission characteristics and sintering performance wer...Process control is an effective approach to reduce the NO_(x) emission from sintering flue gas.The effects of different materials adhered on coke breeze on NO_(x) emission characteristics and sintering performance were studied.Results showed that the coke breeze adhered with the mixture of CaO and Fe_(2)O_(3) or calcium ferrite significantly lowers the NO_(x) emission concentration and conversion ratio of fuel-N to NO_(x).Pretreating the coke with the mixture of lime slurry and iron ore fines helped to improve the granulation effect,and optimize the carbon distribution in granules.When the mass ratio of coke breeze,quick lime,water and iron ore fines was 2:1:1:1,the average NO_(x) emission concentration was decreased from 220 mg/m^(3) to 166 mg/m^(3),and the conversion ratio of fuel-N was reduced from 54.2%to 40.9%.展开更多
The solution purification process is an essential step in zinc hydrometallurgy. The performance of solution purification directly affects the normal functioning and economical benefits of zinc hydrometallurgy. This pa...The solution purification process is an essential step in zinc hydrometallurgy. The performance of solution purification directly affects the normal functioning and economical benefits of zinc hydrometallurgy. This paper summarizes the authors' recent work on the modeling, optimization, and control of solution purification process. The online measurable property of the oxidation reduction potential(ORP) and the multiple reactors, multiple running statuses characteristic of the solution purification process are extensively utilized in this research. The absence of reliable online equipment for detecting the impurity ion concentration is circumvented by introducing the oxidationreduction potential into the kinetic model. A steady-state multiple reactors gradient optimization, unsteady-state operationalpattern adjustment strategy, and a process evaluation strategy based on the oxidation-reduction potential are proposed. The effectiveness of the proposed research is demonstrated by its industrial experiment.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
On the basis of the description of the rare-earth countercurrent extraction process, the on-line detecting method and equipments of rare-earth elements and the application in the process of the rare-earth countercurre...On the basis of the description of the rare-earth countercurrent extraction process, the on-line detecting method and equipments of rare-earth elements and the application in the process of the rare-earth countercurrent extraction are summarized. The procedure simulation of the computer, the automation control method and its current application are also mentioned in the process of rare-earth countercurrent extraction. The method of soft sensor is proposed. Optimal control method based on object-oriented rare-earth countercurrent extraction process and integrated automation system composed of process management system and process control system are presented, which are the developing direction of the automation of rare-earth countercurrent extraction 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
Crystallization is a fundamental separation technology used for the production of particulate solids.Accurate nucleation and growth process control are vitally important but difficult.A novel controlling technology th...Crystallization is a fundamental separation technology used for the production of particulate solids.Accurate nucleation and growth process control are vitally important but difficult.A novel controlling technology that can simultaneously intensify the overall crystallization process remains a significant challenge.Membrane crystallization(MCr),which has progressed significantly in recent years,is a hybrid technology platform with great potential to address this goal.This review illustrates the basic concepts of MCr and its promising applications for crystallization control and process intensification,including a state-of-the-art review of key MCr-utilized membrane materials,process control mechanisms,and optimization strategies based on diverse hybrid membranes and crystallization processes.Finally,efforts to promote MCr technology to industrial use,unexplored issues,and open questions to be addressed are outlined.展开更多
Beacuse the practical mathematic model of rolling process can't be built accurately,this paper established an expert system to control the rolling steels' gauge by adjusting the setup roll open, which combined...Beacuse the practical mathematic model of rolling process can't be built accurately,this paper established an expert system to control the rolling steels' gauge by adjusting the setup roll open, which combined the experience of theoreticians and operators. The system applied the expression method of rule-skeleton+rule-body', and selected an appropriate non-exact reference model and self-study algorithm. The whole system, including auxiliary routes, is designed in Borland C++. Some experiments on this system have been done, and a good result has been achieved.展开更多
On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enha...On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.展开更多
In recent years,the usage,management and benefit of large-scale scientific research instruments and equipment in scientific research institutes have been a leading issue in the management of scientific research instit...In recent years,the usage,management and benefit of large-scale scientific research instruments and equipment in scientific research institutes have been a leading issue in the management of scientific research institutes.Within the scope of equipment budget,it is necessary for each equipment acquisition team to conduct a round of communication,coordination and negotiation with suppliers in order to improve the cost performance of equipment procurement and maximize the performance index to meet the needs of scientific research.By introducing the practical experience of the State Key Laboratory in purchasing imported equipment and managing large-scale instruments,this paper probes into the management process of the imported large-scale scientific research tax-free equipment of scientific research institutes,and explores the system and methods to guarantee and improve the efficiency of large-scale instruments in scientific research institutes from the aspects of policy,funds and technology.展开更多
文摘Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.
基金supported by the National Natural Science Foundation of China(No.51974131)Hebei Outstanding Youth Fund Project(No.E2020209082),Tangshan Key R&D Program project(No.22150232J)Sixth Division Wujiaqu City Science and Technology Plan Project(2410).
文摘During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control in sintering production to keep the mass concentration of NO_(x)in sintering flue gas at a low level.Through industrial trials at sintering sites,methods such as correlation analysis,path analysis,and multiple linear regression were applied to analyze the influence of various factors on NO emissions during the sintering process.The results indicate that negative correlations exist between nitrogen monoxide(NO)emissions and negative pressure,permeability index,O_(2) concentration,CO concentration,and flue gas temperature.Conversely,positive correlations exist between NO emissions and dust concentration,water vapor volume fraction,and sintering bed speed.Among these factors,O_(2) concentration and dust concentration are identified as the most significant influencing factors on NO emissions.By analyzing the masses and modes of influence of different factors,the mechanisms of action of each factor were obtained.Specifically,O_(2) concentration,dust concentration,permeability index,CO concentration,and flue gas temperature play a direct dominant role in NO emissions during the sintering process,while water vapor volume fraction,sintering trolley speed,and negative pressure have an indirect effect.A predictive model for NO mass concentration in flue gas was established with an accuracy rate of 91.6%,showing consistent overall trends with actual values.Finally,denitrification strategies for sintering industrial production were proposed,along with prospects for preliminary denitrification of sintering flue gas using fluidized bed conditions in the duct.
文摘L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.
文摘Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.
文摘Grain size control of tungsten powder is essential for high quality tungsten products. Based on studies on the hydrogen reduction process of tungsten oxide, a microcomputer system is described for reduction process control. The system, now running in Zhuzhou Tungsten and Molybdenum Materials Plant, controls the temperature of the reduction furnace and hydrogen pressure. It also controls a mechanical pusher which pushs the boats charged with blue tungsten oxide into the furnace tubes. Some of the technical problems in the process are analysed.
基金supported by the Central Government Guides Local Science and Technology Development Foundation(No.2023JH6/100100046)the Project funded by China Postdoctoral Science Foundation(No.2023M730230).
文摘A mathematical model of the decarburization reaction zone was established for the Ruhrstahl–Heraeus (RH) forced oxygen blowing decarburization process by Matlab R2022b software. For the problem of inaccurate prediction due to the large variation range of oxygen absorption rate under different process conditions, we statistically analyzed the main factors affecting the oxygen absorption rate. The backpropagation neural network was used to train and predict the oxygen absorption rate and was used to calculate the RH decarburization reaction zone model. We designed and developed a mathematical modeling software with process control of decarburization in RH degasser, which can realize the change of operating process parameters in the dynamic prediction process. The optimized mathematical model has more than 95% of the furnaces whose absolute error in calculation of carbon content is within ± 5 × 10^(−6), more than 90% of the heats whose relative error in calculation of oxygen content is within ± 15%, and the average absolute error of calculation of oxygen content is 26.4 × 10^(−6). Finally, we studied the influence of oxygen blowing timing, oxygen blowing volume and initial oxygen content on the forced decarburization process.
基金the Key Technologies R&D Program of Harbin (0111211102).
文摘The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process
基金Supported by the National Natural Science Foundation of China (No.60374037, No.60574036), the Program for New Century Excellent Talents in University of China (NCET), and the Specialized Research Fund for the Doctoral Program of Higher Edu-cation of China (No.20050055013).
文摘A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.
基金Supported by the Key Agricultral Technology Program of Shanghai Science & Technology Committee(073919108)MajorState Basic Research Development Program of China(2007CB714303)
文摘The methylotrophic yeast Pichia pastoris is a highly successful system for production of a variety of heterologous proteins due to its unique features/abilities for effective protein expression, and tremendous efforts have been made to increase heterologous protein productivity by P. pastoris in recent years. When new engineered yeast strains are constructed and are ready to use tot industrial protein production, process control and optimization techniques should be applied to improve the fermentation performance in the following aspects： （1） increase recombinant cell concentrations in fermentor to high density during growth phase; （2） effectively induce heterologous proteins by enhancing/stabilizing titers or concentrations of the proteins during induction phase; （3） decrease operation costs by relieving the working loads of heat-exchange and oxygen supply. This article reviews and discusses the key and commonly used techniques in heterologous protein production by P. pastoris, with the focus on optimizations of fermentation media and basic operation conditions, development of optimal glycerol feeding strategies for achieving high density cultivation of P. pastoris and effective heterologous protein induction methods by regulating specific growth rate, methanol concentration, temperatures, mixture ratio of multi-carbon substrates, etc. Metabolic analysis for recombinant protein production by P. pastoris is also introduced to interpret the mechanism of sub-optimal heterologous protein production and to explore further optimal expression methods.
基金Supported by the National High Technology Research and Development Program of China（2007AA04Z193） the National Natural Science Foundation of China（60974008 60704032）
文摘For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.
基金the National Natural Science Foundation of China(Nos.51577021 and U1704253)the National Key R&D Program of China(No.2017YFB0703103)the Fundamental Research Funds for the Central Universities(No.DUT20GF111)。
文摘Different amounts of absolute ethanol(0-50 mL)are used as process control agents(PCA)to prepare FeCoNiAlCr0.9 high entropy alloy(HEA)powders via 90 h ball milling.The results show that the increased amount of PCA plays an active role in the crystallinity of powders,and regulate the thickness and size distribution of flake particles.As the volume of PCA increases,the real and imaginary parts(ε′andε″)of complex permittivity get increased by the enhancement of the interface polarization and surface polarization,while the increase in the real and imaginary parts(μ′andμ″)of complex permeability arises from the increased anisotropic energy.The addition of PCA not only promotes the reflection loss but also extends the effective bandwidth(up to 4.28 GHz).Here,the performance adjustment of HEA electromagnetic absorber is realized by forthrightly changing the process parameters of ball milling.
基金Project(2017YFC0210302)supported by the National Key R&D Program of ChinaProjects(U1660206,U1760107)supported by the National Natural Science Foundation of China
文摘Process control is an effective approach to reduce the NO_(x) emission from sintering flue gas.The effects of different materials adhered on coke breeze on NO_(x) emission characteristics and sintering performance were studied.Results showed that the coke breeze adhered with the mixture of CaO and Fe_(2)O_(3) or calcium ferrite significantly lowers the NO_(x) emission concentration and conversion ratio of fuel-N to NO_(x).Pretreating the coke with the mixture of lime slurry and iron ore fines helped to improve the granulation effect,and optimize the carbon distribution in granules.When the mass ratio of coke breeze,quick lime,water and iron ore fines was 2:1:1:1,the average NO_(x) emission concentration was decreased from 220 mg/m^(3) to 166 mg/m^(3),and the conversion ratio of fuel-N was reduced from 54.2%to 40.9%.
基金supported by the National Natural Science Foundation of China(61603418,61673400,61273185)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(61621062)the Innovation-driven Plan in Central South University(2015cx007)
文摘The solution purification process is an essential step in zinc hydrometallurgy. The performance of solution purification directly affects the normal functioning and economical benefits of zinc hydrometallurgy. This paper summarizes the authors' recent work on the modeling, optimization, and control of solution purification process. The online measurable property of the oxidation reduction potential(ORP) and the multiple reactors, multiple running statuses characteristic of the solution purification process are extensively utilized in this research. The absence of reliable online equipment for detecting the impurity ion concentration is circumvented by introducing the oxidationreduction potential into the kinetic model. A steady-state multiple reactors gradient optimization, unsteady-state operationalpattern adjustment strategy, and a process evaluation strategy based on the oxidation-reduction potential are proposed. The effectiveness of the proposed research is demonstrated by its industrial experiment.
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.
文摘On the basis of the description of the rare-earth countercurrent extraction process, the on-line detecting method and equipments of rare-earth elements and the application in the process of the rare-earth countercurrent extraction are summarized. The procedure simulation of the computer, the automation control method and its current application are also mentioned in the process of rare-earth countercurrent extraction. The method of soft sensor is proposed. Optimal control method based on object-oriented rare-earth countercurrent extraction process and integrated automation system composed of process management system and process control system are presented, which are the developing direction of the automation of rare-earth countercurrent extraction 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.
基金We acknowledge the financial contributions from the National Natural Science Foundation of China(21978037,21676043,21527812,and U1663223)the Ministry of Science and Technology of the People’s Republic of China innovation team in key area(2016RA4053)Fundamental Research Funds for the Central Universities(DUT19TD33).
文摘Crystallization is a fundamental separation technology used for the production of particulate solids.Accurate nucleation and growth process control are vitally important but difficult.A novel controlling technology that can simultaneously intensify the overall crystallization process remains a significant challenge.Membrane crystallization(MCr),which has progressed significantly in recent years,is a hybrid technology platform with great potential to address this goal.This review illustrates the basic concepts of MCr and its promising applications for crystallization control and process intensification,including a state-of-the-art review of key MCr-utilized membrane materials,process control mechanisms,and optimization strategies based on diverse hybrid membranes and crystallization processes.Finally,efforts to promote MCr technology to industrial use,unexplored issues,and open questions to be addressed are outlined.
文摘Beacuse the practical mathematic model of rolling process can't be built accurately,this paper established an expert system to control the rolling steels' gauge by adjusting the setup roll open, which combined the experience of theoreticians and operators. The system applied the expression method of rule-skeleton+rule-body', and selected an appropriate non-exact reference model and self-study algorithm. The whole system, including auxiliary routes, is designed in Borland C++. Some experiments on this system have been done, and a good result has been achieved.
基金Item Sponsored by National Natural Science Foundation of China (50527402)
文摘On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.
文摘In recent years,the usage,management and benefit of large-scale scientific research instruments and equipment in scientific research institutes have been a leading issue in the management of scientific research institutes.Within the scope of equipment budget,it is necessary for each equipment acquisition team to conduct a round of communication,coordination and negotiation with suppliers in order to improve the cost performance of equipment procurement and maximize the performance index to meet the needs of scientific research.By introducing the practical experience of the State Key Laboratory in purchasing imported equipment and managing large-scale instruments,this paper probes into the management process of the imported large-scale scientific research tax-free equipment of scientific research institutes,and explores the system and methods to guarantee and improve the efficiency of large-scale instruments in scientific research institutes from the aspects of policy,funds and technology.
