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
This article explores controllable Borel spaces, stationary, homogeneous Markov processes, discrete time with infinite horizon, with bounded cost functions and using the expected total discounted cost criterion. The p...This article explores controllable Borel spaces, stationary, homogeneous Markov processes, discrete time with infinite horizon, with bounded cost functions and using the expected total discounted cost criterion. The problem of the estimation of stability for this type of process is set. The central objective is to obtain a bounded stability index expressed in terms of the Lévy-Prokhorov metric;likewise, sufficient conditions are provided for the existence of such inequalities.展开更多
In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary poli...In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary policies and for the value functions, the stability index is explicitly calculated and through statistical techniques its asymptotic behavior is investigated (using numerical experiments) when the discount coefficient approaches 1. The results obtained define the conditions under which an approximate optimal stationary policy can be used to control the original process.展开更多
As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the...As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the leading cause.Hence,the solution may rest with the synchronization of those heating processes in MCHR system.This paper proposes a’Master-Slave’generalized predictive synchronization control(MS-GPSC)method with’Mr.Slowest’strategy for preheating stage of MCHR system.The core of the proposed method is choosing the heating process with slowest dynamics as the’Master’to track the setpoint,while the other heating processes are treated as‘Slaves’tracking the output of’Master’.This proposed method is shown to have the good ability of temperature synchronization.The corresponding analysis is conducted on parameters tuning and stability,simulations and experiments show the strategy is effective.展开更多
This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control ...This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.展开更多
Probabilistic Fault Recoverability(FR) property reveals the capability of a system to accommodate faults under admissible input energy constraints in the sense of satisfactory probability. Motivated by the idea of pro...Probabilistic Fault Recoverability(FR) property reveals the capability of a system to accommodate faults under admissible input energy constraints in the sense of satisfactory probability. Motivated by the idea of probabilistic control methods, a class of admissible probability density functions is designed for detailed description of fault parameters, under which several probabilistic FR conditions are established. This significantly enlarges the range of recoverable faults obtained from the deterministic FR analysis. The tradeoffs between the risk of performance degradation and this increased recoverability margin are exactly achieved by allowing a small risk of FR violation. This paper analyzes the probability FR of dynamic systems with switching and interconnection characteristics, and applies the new results to several aircraft models including single longitudinal aircraft dynamic, Highly Maneuverable Technology(HiMAT) vehicle and meta aircraft. Simulation results show the efficiency of the proposed methods based on the comparison between deterministic and probabilistic cases.展开更多
Low carbon steels microalloyed with small amount of carbide and/or nitride forming elements such as Nb,Ti and V with Thermomechanical controlled processing (TMCP) can give fine grained ferrite structure with high stre...Low carbon steels microalloyed with small amount of carbide and/or nitride forming elements such as Nb,Ti and V with Thermomechanical controlled processing (TMCP) can give fine grained ferrite structure with high strength and superior toughness.The present study was aimed at identifying rolling parameters as well as microstructural characterization for accomplishing high yield strength and high charpy impact property at-60℃ by controlling hot rolling parameters and microstructure Grain size distribution was also monitored and related to mechanical properties of steel.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
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
In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the wh...In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.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
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
Effect of controlled rolling and cooling process on the mechanical properties of low carbon cold forging steel was investigated for different processing parameters of a laboratory hot rolling mill. The results show th...Effect of controlled rolling and cooling process on the mechanical properties of low carbon cold forging steel was investigated for different processing parameters of a laboratory hot rolling mill. The results show that the specimens with fast cooling after hot rolling exhibit very good mechanical properties, and the improvement of the mechanical properties can be attributed mainly to the ferrite-grain refinement. The mechanical properties increase with decreasing final cooling temperature within the range from 670 ℃ to 570 ℃ due to the finer interlamellar spacing of pearlite colony. The specimen with fast cooling after low temperature rolling shows the highest values of the mechanical properties. The effect of the ferrite grain size on the mechanical properties was greater than that of pearlite morphology in the present study. The mechanical properties of specimens by controlled rolling and cooling process without thermal treatment were greatly superior to that of the same specimens by the conventional rolling, and their tensile strength reached 490 MPa grade even in the case of low temperature rolling without controlled rolling. It might be expected to realize the substitution medium-carbon by low-carbon for 490 MPa grade cold forging steel with controlled rolling and cooling process.展开更多
The physical properties of thermosetting resins and resin based composites may be influenced by changes in any one of the mang formulating or process related variables involved in their manufacture. When resins and co...The physical properties of thermosetting resins and resin based composites may be influenced by changes in any one of the mang formulating or process related variables involved in their manufacture. When resins and composite materials are required to perform in aggressive environments, reliable and predicable performance is essential and therefore these materials must be prepared and tested in accorkance with a strictquality plan. This paper outlines the elements of statistical process control (S.P.C.)as it may be applied to non-metallic materials and discusses the concept of Capability Index (Cp).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
Better flexibility and controllability have been introduced into distribution system with the development of new loads and resources.As a consequence,the connotations and tools for evaluating the planning solution nee...Better flexibility and controllability have been introduced into distribution system with the development of new loads and resources.As a consequence,the connotations and tools for evaluating the planning solution need to be further enriched.This paper proposes a fast algorithm to quantify steady-state voltages and load profiles in distribution system by simulating the manipulation control process of controllable resources,taking the efficiency and ease of use into account.In this method,a complex distribution system is decoupled into several simple parts according to the ports of the DC interlink.Then,to achieve the qualified voltages and load profiles,the manipulation details of controllable resources are simulated following a certain control sequence in each part.Finally,the analysis results of each part are matched and filtered to obtain a complete evaluation.Five types of the most commonly controllable resources are considered in this method.The effectiveness of the proposed method is demonstrated through a case study based on field data from an actual distribution system.展开更多
Anomaly detection is becoming increasingly significant in industrial cyber security,and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to succes...Anomaly detection is becoming increasingly significant in industrial cyber security,and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks.However,different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples.As a sequence,after developing one feature generation approach,the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm.Based on process control features generated by directed function transition diagrams,this paper introduces five different machine-learning algorithms as alternative detection engines to discuss their matching abilities.Furthermore,this paper not only describes some qualitative properties to compare their advantages and disadvantages,but also gives an in-depth and meticulous research on their detection accuracies and consuming time.In the verified experiments,two attack models and four different attack intensities are defined to facilitate all quantitative comparisons,and the impacts of detection accuracy caused by the feature parameter are also comparatively analyzed.All experimental results can clearly explain that SVM(Support Vector Machine)and WNN(Wavelet Neural Network)are suggested as two applicable detection engines under differing cases.展开更多
Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinea...Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors.展开更多
Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic n...Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.展开更多
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.
文摘This article explores controllable Borel spaces, stationary, homogeneous Markov processes, discrete time with infinite horizon, with bounded cost functions and using the expected total discounted cost criterion. The problem of the estimation of stability for this type of process is set. The central objective is to obtain a bounded stability index expressed in terms of the Lévy-Prokhorov metric;likewise, sufficient conditions are provided for the existence of such inequalities.
文摘In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary policies and for the value functions, the stability index is explicitly calculated and through statistical techniques its asymptotic behavior is investigated (using numerical experiments) when the discount coefficient approaches 1. The results obtained define the conditions under which an approximate optimal stationary policy can be used to control the original process.
基金supported in part by National Natural Science Foundation of China(62203127)Basic and Applied Basic Research Project of Guangzhou City(2023A04J1712)+1 种基金The Foshan-HKUST Projects Program(FSUST19-FYTRI01)GDAS’Project of Science and Technology Development(2020GDASYL-20200202001).
文摘As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the leading cause.Hence,the solution may rest with the synchronization of those heating processes in MCHR system.This paper proposes a’Master-Slave’generalized predictive synchronization control(MS-GPSC)method with’Mr.Slowest’strategy for preheating stage of MCHR system.The core of the proposed method is choosing the heating process with slowest dynamics as the’Master’to track the setpoint,while the other heating processes are treated as‘Slaves’tracking the output of’Master’.This proposed method is shown to have the good ability of temperature synchronization.The corresponding analysis is conducted on parameters tuning and stability,simulations and experiments show the strategy is effective.
基金supported in part by the Natural Sciences Engineering Research Council of Canada (NSERC)。
文摘This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.
基金supported by National Natural Science Foundation of China (Nos. 61773201, 62073165)the 111 Project,China (No. B20007)the Fundamental Research Funds for the Central Universities, China (No. NZ2020003)。
文摘Probabilistic Fault Recoverability(FR) property reveals the capability of a system to accommodate faults under admissible input energy constraints in the sense of satisfactory probability. Motivated by the idea of probabilistic control methods, a class of admissible probability density functions is designed for detailed description of fault parameters, under which several probabilistic FR conditions are established. This significantly enlarges the range of recoverable faults obtained from the deterministic FR analysis. The tradeoffs between the risk of performance degradation and this increased recoverability margin are exactly achieved by allowing a small risk of FR violation. This paper analyzes the probability FR of dynamic systems with switching and interconnection characteristics, and applies the new results to several aircraft models including single longitudinal aircraft dynamic, Highly Maneuverable Technology(HiMAT) vehicle and meta aircraft. Simulation results show the efficiency of the proposed methods based on the comparison between deterministic and probabilistic cases.
文摘Low carbon steels microalloyed with small amount of carbide and/or nitride forming elements such as Nb,Ti and V with Thermomechanical controlled processing (TMCP) can give fine grained ferrite structure with high strength and superior toughness.The present study was aimed at identifying rolling parameters as well as microstructural characterization for accomplishing high yield strength and high charpy impact property at-60℃ by controlling hot rolling parameters and microstructure Grain size distribution was also monitored and related to mechanical properties of steel.
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The authors acknowledge financial support for this research from the National Key Research and Development Program of China(2017YFB0403300 and 2017YFB043305)the National Natural Science Foundation of China(51425405 and 51874269),the National Science-Technology Support Plan Projects(2015BAB02B05)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2014037).Zhi Sun acknowledges financial support from the National Youth Thousand Talents Program.The authors acknowledge constructive suggestions from Prof.Jianxin Yang.
文摘In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.
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.
基金Funded by Shenyang City Application Basic Research Project (No. 1071198-1-00)
文摘Effect of controlled rolling and cooling process on the mechanical properties of low carbon cold forging steel was investigated for different processing parameters of a laboratory hot rolling mill. The results show that the specimens with fast cooling after hot rolling exhibit very good mechanical properties, and the improvement of the mechanical properties can be attributed mainly to the ferrite-grain refinement. The mechanical properties increase with decreasing final cooling temperature within the range from 670 ℃ to 570 ℃ due to the finer interlamellar spacing of pearlite colony. The specimen with fast cooling after low temperature rolling shows the highest values of the mechanical properties. The effect of the ferrite grain size on the mechanical properties was greater than that of pearlite morphology in the present study. The mechanical properties of specimens by controlled rolling and cooling process without thermal treatment were greatly superior to that of the same specimens by the conventional rolling, and their tensile strength reached 490 MPa grade even in the case of low temperature rolling without controlled rolling. It might be expected to realize the substitution medium-carbon by low-carbon for 490 MPa grade cold forging steel with controlled rolling and cooling process.
文摘The physical properties of thermosetting resins and resin based composites may be influenced by changes in any one of the mang formulating or process related variables involved in their manufacture. When resins and composite materials are required to perform in aggressive environments, reliable and predicable performance is essential and therefore these materials must be prepared and tested in accorkance with a strictquality plan. This paper outlines the elements of statistical process control (S.P.C.)as it may be applied to non-metallic materials and discusses the concept of Capability Index (Cp).
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.
基金supported by National Key Research and Development Program(No.2017YFB0903300)National Natural Science Foundation of China(No.51777105).
文摘Better flexibility and controllability have been introduced into distribution system with the development of new loads and resources.As a consequence,the connotations and tools for evaluating the planning solution need to be further enriched.This paper proposes a fast algorithm to quantify steady-state voltages and load profiles in distribution system by simulating the manipulation control process of controllable resources,taking the efficiency and ease of use into account.In this method,a complex distribution system is decoupled into several simple parts according to the ports of the DC interlink.Then,to achieve the qualified voltages and load profiles,the manipulation details of controllable resources are simulated following a certain control sequence in each part.Finally,the analysis results of each part are matched and filtered to obtain a complete evaluation.Five types of the most commonly controllable resources are considered in this method.The effectiveness of the proposed method is demonstrated through a case study based on field data from an actual distribution system.
基金This work is supported by the Scientific Research Project of Educational Department of Liaoning Province(Grant No.LJKZ0082)the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(Grant No.QCXM201910)+2 种基金the National Natural Science Foundation of China(Grant Nos.61802092 and 92067110)the Hainan Provincial Natural Science Foundation of China(Grant No.620RC562)2020 Industrial Internet Innovation and Development Project-Industrial Internet Identification Data Interaction Middleware and Resource Pool Service Platform Project,Ministry of Industry and Information Technology of the People’s Republic of China.
文摘Anomaly detection is becoming increasingly significant in industrial cyber security,and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks.However,different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples.As a sequence,after developing one feature generation approach,the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm.Based on process control features generated by directed function transition diagrams,this paper introduces five different machine-learning algorithms as alternative detection engines to discuss their matching abilities.Furthermore,this paper not only describes some qualitative properties to compare their advantages and disadvantages,but also gives an in-depth and meticulous research on their detection accuracies and consuming time.In the verified experiments,two attack models and four different attack intensities are defined to facilitate all quantitative comparisons,and the impacts of detection accuracy caused by the feature parameter are also comparatively analyzed.All experimental results can clearly explain that SVM(Support Vector Machine)and WNN(Wavelet Neural Network)are suggested as two applicable detection engines under differing cases.
文摘Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors.
基金Supported by National Natural Science Foundation of China (No. 70931004)
文摘Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.