The Experts below are selected from a list of 263151 Experts worldwide ranked by ideXlab platform
Chunhua Yang - One of the best experts on this subject based on the ideXlab platform.
-
fractional order fuzzy pid optimal control in copper Removal Process of zinc hydrometallurgy
Hydrometallurgy, 2018Co-Authors: Fengxue Zhang, Chunhua Yang, Xiaojun Zhou, Hongqiu ZhuAbstract:Abstract The copper Removal Process is the first stage of purification in zinc hydrometallurgy. Due to its dynamic characteristics and complex reaction mechanism, a robust and effective controller to maintain high quality and stability of the outlet-ion-concentration is in great need. In this paper, a fractional order fuzzy proportional integral derivative (FOFPID) controller based on fuzzy logic is proposed to meet this challenge. The proposed work is conducted through a combination of three novel interdependent efforts. First, controller design problem is transformed into a nonconvex optimization problem. Second, a novel method named state transition algorithm (STA) is employed to solve the aforementioned optimization problem. Furthermore, in order to evaluate the performance of the proposed control strategy, the response performance of the system is analyzed. Finally, further tests are carried out to evaluate the performance of FOFPID controller, where disturbances caused by the measurement, flow rate, and inlet-ion-concentration are all taken into account. The simulation results demonstrate the superiority of the FOFPID controller in copper Removal Process over the competing FOPID and manual control in the same application environment.
-
a hybrid control strategy for real time control of the iron Removal Process of the zinc hydrometallurgy plants
IEEE Transactions on Industrial Informatics, 2018Co-Authors: Shiwen Xie, Weihua Gui, Yongfang Xie, Hao Ying, Chunhua YangAbstract:As part of the zinc hydrometallurgy plant, the iron Removal Process is a complex system with four cascaded reactors. Tighter Process-index control is difficult to achieve due to the complicated, long, and time-varying Removal Process. The control performance is also affected by the quality of the ore source and external disturbances. Little research is documented in the literature to address these difficulties and manual control is widely used. An innovative hybrid control strategy is developed to control the iron Removal Process’ indices within narrow ranges with minimum cost of additive regents, including oxygen and zinc oxide. This strategy is composed of an optimal setting model, a model-based optimal controller, an integrated prediction model, a fuzzy-logic-based feedforward compensator, and a model feedback adjustor. The optimal setting model automatically optimizes the set-points of the Process indices under different production conditions. To achieve the Process requirements with minimal cost, the model-based optimal controller is designed. The integrated prediction model is established to provide a more accurate on-line prediction of the Process indices by integrating the mechanism prediction model and an error compensation model based on the least-square support vector machine. Based on the predicted Process indices, the compensator is developed for the optimal controller. The adjustor provides a parameter adjustment mechanism. Four-week-long industrial experiments in the largest zinc hydrometallurgy plant in China show that the control strategy can not only improve the Process-indexes control performance, but also save 6.55% oxygen and 4.61% zinc oxide consumptions, which translates to 222 858 m3 oxygen and 1236 t zinc oxide per year (a saving of about $570 000). The hybrid control strategy can be extended to cover other similar Processes in the zinc hydrometallurgy and other industries.
-
Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Peng Shi, Weihua GuiAbstract:In copper Removal Process control, the commonly used technique is the so-called rule-based control, which is largely dependent upon the operators' experience, likely leading to unstable Process production due to each individual's characters and favors. In this paper, to enhance the effectiveness of Process control, a controllable-domain-based fuzzy rule extraction strategy is proposed. New definitions of representative controlled samples are introduced, by which the input variable space is divided into several controllable domains by applying positive and unlabeled learning algorithm. Also, the unreasonable removed and the controllable domains are accordingly determined. Then, support vector machine method is employed to extract fuzzy control rules for different domains. Finally, an industrial experiment is presented to demonstrate the effectiveness and advantages of the developed new design scheme.
-
evaluation strategy for the control of the copper Removal Process based on oxidation reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
control strategy for hydrometallurgical Removal Process based on modelling and evaluation
IFAC-PapersOnLine, 2016Co-Authors: Bin Zhang, Chunhua YangAbstract:Abstract: Impurity Removal is an essential stage in non-ferrous metal hydrometallurgy. The control Removal Process influences the stability and production qualification of the whole Process. To enhance the Removal Process stability, a control strategy based on modelling and evaluation is proposed in this paper. The strategy consists of two level controls: an optimal control based on Process model and an expert control based Process evaluation. The optimal control sets major amounts for control variables in the Removal Process, while the expert control adjusts the amounts with online evaluation results. The proposed strategy is performed on the copper Removal Process of zinc hydrometallurgy, and the experiment result proves its effectiveness.
Weihua Gui - One of the best experts on this subject based on the ideXlab platform.
-
a hybrid control strategy for real time control of the iron Removal Process of the zinc hydrometallurgy plants
IEEE Transactions on Industrial Informatics, 2018Co-Authors: Shiwen Xie, Weihua Gui, Yongfang Xie, Hao Ying, Chunhua YangAbstract:As part of the zinc hydrometallurgy plant, the iron Removal Process is a complex system with four cascaded reactors. Tighter Process-index control is difficult to achieve due to the complicated, long, and time-varying Removal Process. The control performance is also affected by the quality of the ore source and external disturbances. Little research is documented in the literature to address these difficulties and manual control is widely used. An innovative hybrid control strategy is developed to control the iron Removal Process’ indices within narrow ranges with minimum cost of additive regents, including oxygen and zinc oxide. This strategy is composed of an optimal setting model, a model-based optimal controller, an integrated prediction model, a fuzzy-logic-based feedforward compensator, and a model feedback adjustor. The optimal setting model automatically optimizes the set-points of the Process indices under different production conditions. To achieve the Process requirements with minimal cost, the model-based optimal controller is designed. The integrated prediction model is established to provide a more accurate on-line prediction of the Process indices by integrating the mechanism prediction model and an error compensation model based on the least-square support vector machine. Based on the predicted Process indices, the compensator is developed for the optimal controller. The adjustor provides a parameter adjustment mechanism. Four-week-long industrial experiments in the largest zinc hydrometallurgy plant in China show that the control strategy can not only improve the Process-indexes control performance, but also save 6.55% oxygen and 4.61% zinc oxide consumptions, which translates to 222 858 m3 oxygen and 1236 t zinc oxide per year (a saving of about $570 000). The hybrid control strategy can be extended to cover other similar Processes in the zinc hydrometallurgy and other industries.
-
Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Peng Shi, Weihua GuiAbstract:In copper Removal Process control, the commonly used technique is the so-called rule-based control, which is largely dependent upon the operators' experience, likely leading to unstable Process production due to each individual's characters and favors. In this paper, to enhance the effectiveness of Process control, a controllable-domain-based fuzzy rule extraction strategy is proposed. New definitions of representative controlled samples are introduced, by which the input variable space is divided into several controllable domains by applying positive and unlabeled learning algorithm. Also, the unreasonable removed and the controllable domains are accordingly determined. Then, support vector machine method is employed to extract fuzzy control rules for different domains. Finally, an industrial experiment is presented to demonstrate the effectiveness and advantages of the developed new design scheme.
-
evaluation strategy for the control of the copper Removal Process based on oxidation reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
Evaluation strategy for the control of the copper Removal Process based on oxidation–reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
Intelligent optimal setting control of a cobalt Removal Process
Journal of Process Control, 2014Co-Authors: Bei Sun, Weihua Gui, Yalin Wang, Chunhua YangAbstract:Abstract Cobalt Removal Process is an important step in zinc hydrometallurgy. Because of its complex reaction mechanism and dynamic characteristics, human supervision with low level control is not sufficient to keep the stable and optimal operation of cobalt Removal Process. This paper presents an intelligent optimal setting control strategy of cobalt Removal Process. The control strategy consists of Process monitoring unit, zinc dust utilization factor (ZDUF) estimation unit, cobalt Removal ratio (CRR) optimal setting unit, oxidation reduction potential (ORP) setting unit and case based reasoning (CBR) controller. Process monitoring unit judges the state of current Process. When Process is at steady state, economical optimization is conducted by allocating suitable CRR to reactors according to their ZDUF. In order to realize automatic control, CRR is transformed into the setting value of ORP through an integrated model which is also able to estimate outlet cobalt ion concentration. When a Process is at an abnormal state, case based reasoning controller is triggered to handle the undesired situation by providing rational solution of control variables. An industrial experiment shows that by using the proposed control strategy, zinc dust consumption can be reduced while the required cobalt Removal performance is always achieved. Stability of cobalt Removal can also be improved by limiting CRR of each reactor in predefined ranges.
Bin Zhang - One of the best experts on this subject based on the ideXlab platform.
-
Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Peng Shi, Weihua GuiAbstract:In copper Removal Process control, the commonly used technique is the so-called rule-based control, which is largely dependent upon the operators' experience, likely leading to unstable Process production due to each individual's characters and favors. In this paper, to enhance the effectiveness of Process control, a controllable-domain-based fuzzy rule extraction strategy is proposed. New definitions of representative controlled samples are introduced, by which the input variable space is divided into several controllable domains by applying positive and unlabeled learning algorithm. Also, the unreasonable removed and the controllable domains are accordingly determined. Then, support vector machine method is employed to extract fuzzy control rules for different domains. Finally, an industrial experiment is presented to demonstrate the effectiveness and advantages of the developed new design scheme.
-
An optimal control strategy for hydrometallurgical Removal Process under uncertainty
IFAC-PapersOnLine, 2018Co-Authors: Bin Zhang, Yiting LiangAbstract:Abstract Impurity Removal of hydrometallurgy, focused on reducing the ionic impurities with various additives, is critical stage to determine the production quality and stability. Due to the uncertainty and disturbances in the Process, these impurities could rarely be purified effectively which easily results in a poor product quality of hydrometallurgy. To improve the impurity Removal production, an optimal control strategy is proposed for Removal Process under uncertainty. In this strategy, the distribution probability of Process uncertainty and disturbances are estimated and introduced into Process optimization. And then a pair of relaxing variables is defined to adjust the production constraints for obtaining a feasible optimal solution under uncertainty. The proposed strategy is performed with industrial samples from a practical Removal Process, and the experiment result proves its effectiveness.
-
evaluation strategy for the control of the copper Removal Process based on oxidation reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
control strategy for hydrometallurgical Removal Process based on modelling and evaluation
IFAC-PapersOnLine, 2016Co-Authors: Bin Zhang, Chunhua YangAbstract:Abstract: Impurity Removal is an essential stage in non-ferrous metal hydrometallurgy. The control Removal Process influences the stability and production qualification of the whole Process. To enhance the Removal Process stability, a control strategy based on modelling and evaluation is proposed in this paper. The strategy consists of two level controls: an optimal control based on Process model and an expert control based Process evaluation. The optimal control sets major amounts for control variables in the Removal Process, while the expert control adjusts the amounts with online evaluation results. The proposed strategy is performed on the copper Removal Process of zinc hydrometallurgy, and the experiment result proves its effectiveness.
-
Evaluation strategy for the control of the copper Removal Process based on oxidation–reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
Hongqiu Zhu - One of the best experts on this subject based on the ideXlab platform.
-
fractional order fuzzy pid optimal control in copper Removal Process of zinc hydrometallurgy
Hydrometallurgy, 2018Co-Authors: Fengxue Zhang, Chunhua Yang, Xiaojun Zhou, Hongqiu ZhuAbstract:Abstract The copper Removal Process is the first stage of purification in zinc hydrometallurgy. Due to its dynamic characteristics and complex reaction mechanism, a robust and effective controller to maintain high quality and stability of the outlet-ion-concentration is in great need. In this paper, a fractional order fuzzy proportional integral derivative (FOFPID) controller based on fuzzy logic is proposed to meet this challenge. The proposed work is conducted through a combination of three novel interdependent efforts. First, controller design problem is transformed into a nonconvex optimization problem. Second, a novel method named state transition algorithm (STA) is employed to solve the aforementioned optimization problem. Furthermore, in order to evaluate the performance of the proposed control strategy, the response performance of the system is analyzed. Finally, further tests are carried out to evaluate the performance of FOFPID controller, where disturbances caused by the measurement, flow rate, and inlet-ion-concentration are all taken into account. The simulation results demonstrate the superiority of the FOFPID controller in copper Removal Process over the competing FOPID and manual control in the same application environment.
-
Controllable-Domain-Based Fuzzy Rule Extraction for Copper Removal Process Control
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Peng Shi, Weihua GuiAbstract:In copper Removal Process control, the commonly used technique is the so-called rule-based control, which is largely dependent upon the operators' experience, likely leading to unstable Process production due to each individual's characters and favors. In this paper, to enhance the effectiveness of Process control, a controllable-domain-based fuzzy rule extraction strategy is proposed. New definitions of representative controlled samples are introduced, by which the input variable space is divided into several controllable domains by applying positive and unlabeled learning algorithm. Also, the unreasonable removed and the controllable domains are accordingly determined. Then, support vector machine method is employed to extract fuzzy control rules for different domains. Finally, an industrial experiment is presented to demonstrate the effectiveness and advantages of the developed new design scheme.
-
evaluation strategy for the control of the copper Removal Process based on oxidation reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
Evaluation strategy for the control of the copper Removal Process based on oxidation–reduction potential
Chemical Engineering Journal, 2016Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:Abstract The copper Removal Process purifies copper from leaching solutions with zinc powder in reactors. Due to the complex reaction mechanism and unavailability of online measurements, zinc powder is usually added inexactly, which easily leads to unstable production. This paper proposes an online evaluation method based on oxidation–reduction potential (ORP) for the control of the copper Removal Process. A kinetic model is designed to translate the production requirements to evaluation indexes of ORP, and the Process is then graded by evaluating the fuzzified ORP and its trends according to these indexes. By analyzing these evaluation grades, the Process condition is divided into several classes, and each condition class corresponds to a control method set. The industrial experiments show that the copper Removal performance is improved by using the proposed evaluation and control strategy.
-
kinetic modeling and parameter estimation for competing reactions in copper Removal Process from zinc sulfate solution
Industrial & Engineering Chemistry Research, 2013Co-Authors: Bin Zhang, Chunhua Yang, Hongqiu Zhu, Weihua GuiAbstract:In zinc hydrometallurgy, an advanced copper Removal Process purifies zinc sulfate solution through a series of chemical reactions with recycled underflow by using zinc powder in zinc hydrometallurg...
Yonggang Li - One of the best experts on this subject based on the ideXlab platform.
-
kinetic modeling and parameter estimation for competing reactions in copper Removal Process from zinc sulfate solution
Industrial & Engineering Chemistry Research, 2013Co-Authors: Bin Zhang, Chunhua Yang, Yonggang LiAbstract:In zinc hydrometallurgy, an advanced copper Removal Process purifies zinc sulfate solution through a series of chemical reactions with recycled underflow by using zinc powder in zinc hydrometallurgy. This paper focuses on the kinetic modeling of the competitive-consecutive reaction system in the copper Removal Process, and proposes an adaptive parameter optimal selection strategy for different industrial conditions. In the system model, copper cementation, one of the Removal reactions, is described by a surface controlled pseudo-first-order rate equation; cuprous oxide precipitation, the other Removal reaction, is described by a shrinking core model of a noncatalytic fluid–solid reaction. Because there are several kinetic parameters in the system model, parameter estimation plays an essential role. Because of the complexity and variation in the practical Removal Process, the kinetic parameters are usually sensitive to alterations in the Process conditions. This work solves the parameter estimation problem...
