The Experts below are selected from a list of 1923 Experts worldwide ranked by ideXlab platform
Daniel Hodouin - One of the best experts on this subject based on the ideXlab platform.
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economic optimisation of a flotation plant through Grinding Circuit tuning
Minerals Engineering, 2000Co-Authors: C Sosablanco, Daniel Hodouin, Claude Bazin, C Laravalenzuela, J SalazarAbstract:Abstract The paper describes a procedure to tune a Grinding Circuit in order to maximise the economic efficiency of the flotation plant. The optimisation process is performed using a plant simulator based on phenomenological models of Grinding and flotation and an empirical model for predicting the minerals size distribution from the ore size distribution of the Grinding Circuit product. The economic efficiency of the plant is assessed either by the net smelter return per ton of ore or the net revenue of the concentrator. The approach is illustrated for a lead silver gold plant located in Mexico and shows that the economic efficiency of this plant could be increased by 10 to 20%.
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A survey of Grinding Circuit control methods: from decentralized PID controllers to multivariable predictive controllers
Powder Technology, 2000Co-Authors: André Pomerleau, Daniel Hodouin, André Desbiens, Eric GagnonAbstract:Abstract A conventional Grinding Circuit consisting of one open-loop rod mill and one closed-loop ball mill is essentially a two-input×two-output system, assuming that the classifier pump box level is controlled by a local loop. The inputs are the ore and water feed rates and the outputs are the product fineness and the circulating load. The design problem is to find a control algorithm and a tuning procedure which satisfy specified servo and regulatory robust performances. A first approach is to use decentralized PID controllers and systematic tuning methods which take into account loop interactions. Another technique consists of adding decouplers or pseudo-decouplers to the decentralized controllers. Finally, the design of a fully multivariable controller is a possible option. To face the problem of performance robustness related to change of process dynamics, two options are studied. A design criterion involving the minimization of a penalized quadratic function on a future trajectory can be used. A second alternative is to track process dynamics changes using adaptive process modelling. The paper will present a comparison of these various strategies, for a simulated Grinding Circuit. A benchmark test, involving a sequence of disturbances (grindability, feed size distribution, change of cyclone number…) and setpoint changes, is used to compare the performances of the controllers.
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Robust Control of Ill-Conditioned Plant: Grinding Circuit
IFAC Proceedings Volumes, 2000Co-Authors: S. Yahmedi, André Pomerleau, Daniel HodouinAbstract:Abstract Modern controllers are based on the use of mathematical models. However the models are always obtained through a reduction in the complexity of reality. Consequently, their ability to properly represent the general behavior of the processes is very limited. Therefore, it is advantageous to analyze the problem resulting from model uncertainty in the control of ill conditioned plant: Grinding Circuit. This problem has often been ignored in theoretical studies and in practical process control. This paper will first show a LQG/LTR method on how to achieve the benefit of feedback in the face of uncertainties. Then it will present Grinding process example which illustrates the use of robust control to provide satisfactory performance despite of system uncertainties in mineral processing plant.
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LQG/LTR Control of Ill-Conditioned Plant: Grinding Circuit
IFAC Proceedings Volumes, 2000Co-Authors: S. Yahmedi, C. Pomerleau, Daniel HodouinAbstract:Abstract Modem controllers are based on the use of mathematical models. However the models are always obtained through a reduction in the complexity of reality. Consequently, their ability to properly represent the general behavior of the processes is very limited. Therefore, it is advantageous to analyze the problem resulting from model uncertainty in the control of ill conditioned plant: Grinding Circuit. This problem has often been ignored in theoretical studies and in practical process control. This paper will first show a LQG/LTR method on how to achieve the benefit of feedback in the face of uncertainties. Then it will present Grinding process example which illustrates the use of robust control to provide satisfactory performance despite of system uncertainties in mineral processing plant.
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Robust Controllers for Grinding Circuit
IFAC Proceedings Volumes, 1998Co-Authors: S. Yahmedi, André Pomerleau, Daniel HodouinAbstract:Abstract In this paper, the results of a study into the use of Η∞ and LQG/LTR methods for the design of robust feedback control laws to provide satisfactory performance despite of system uncertainties in Grinding Circuit are presented. Robust controllers are designed to give accurate control of ball mill throughput and product fineness. The design is based on a linear model obtained from a phenomenological simulator of Grinding Circuit. Robustness is a major issue because changes in operating conditions are not included in the design model. Robust stability and performance are assessed from singular values plots. Simulations show a better performance of H∞ synthesis when compared to a LQG/LTR controller.
André Pomerleau - One of the best experts on this subject based on the ideXlab platform.
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A survey of Grinding Circuit control methods: from decentralized PID controllers to multivariable predictive controllers
Powder Technology, 2000Co-Authors: André Pomerleau, Daniel Hodouin, André Desbiens, Eric GagnonAbstract:Abstract A conventional Grinding Circuit consisting of one open-loop rod mill and one closed-loop ball mill is essentially a two-input×two-output system, assuming that the classifier pump box level is controlled by a local loop. The inputs are the ore and water feed rates and the outputs are the product fineness and the circulating load. The design problem is to find a control algorithm and a tuning procedure which satisfy specified servo and regulatory robust performances. A first approach is to use decentralized PID controllers and systematic tuning methods which take into account loop interactions. Another technique consists of adding decouplers or pseudo-decouplers to the decentralized controllers. Finally, the design of a fully multivariable controller is a possible option. To face the problem of performance robustness related to change of process dynamics, two options are studied. A design criterion involving the minimization of a penalized quadratic function on a future trajectory can be used. A second alternative is to track process dynamics changes using adaptive process modelling. The paper will present a comparison of these various strategies, for a simulated Grinding Circuit. A benchmark test, involving a sequence of disturbances (grindability, feed size distribution, change of cyclone number…) and setpoint changes, is used to compare the performances of the controllers.
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Robust Control of Ill-Conditioned Plant: Grinding Circuit
IFAC Proceedings Volumes, 2000Co-Authors: S. Yahmedi, André Pomerleau, Daniel HodouinAbstract:Abstract Modern controllers are based on the use of mathematical models. However the models are always obtained through a reduction in the complexity of reality. Consequently, their ability to properly represent the general behavior of the processes is very limited. Therefore, it is advantageous to analyze the problem resulting from model uncertainty in the control of ill conditioned plant: Grinding Circuit. This problem has often been ignored in theoretical studies and in practical process control. This paper will first show a LQG/LTR method on how to achieve the benefit of feedback in the face of uncertainties. Then it will present Grinding process example which illustrates the use of robust control to provide satisfactory performance despite of system uncertainties in mineral processing plant.
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Robust Controllers for Grinding Circuit
IFAC Proceedings Volumes, 1998Co-Authors: S. Yahmedi, André Pomerleau, Daniel HodouinAbstract:Abstract In this paper, the results of a study into the use of Η∞ and LQG/LTR methods for the design of robust feedback control laws to provide satisfactory performance despite of system uncertainties in Grinding Circuit are presented. Robust controllers are designed to give accurate control of ball mill throughput and product fineness. The design is based on a linear model obtained from a phenomenological simulator of Grinding Circuit. Robustness is a major issue because changes in operating conditions are not included in the design model. Robust stability and performance are assessed from singular values plots. Simulations show a better performance of H∞ synthesis when compared to a LQG/LTR controller.
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Advanced Control of an Industrial Closed-Loop Grinding Circuit
IFAC Proceedings Volumes, 1998Co-Authors: Richard Lestage, André Pomerleau, Gaétan J. LavoieAbstract:Abstract This paper gives an industrial application of advanced control strategies using basic functions available in distributed control systems (DCS). The process under study is an industrial full-scale closed-loop Grinding Circuit where pulp solid mass fraction is to be controlled at the mill and at the cyclones. An algebraic implementation of a Kalman filter is used to evaluate the unmeasured pulp solid mass fraction at the mill discharge using mass balance relations. A static decoupler is used to eliminate the interaction between the two controlled variables. Open-loop adaptation is used to take into account the non-linearity of the process in conjunction with an internal model controller.
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Adaptive control—practical aspects and application to a Grinding Circuit
Optimal Control Applications and Methods, 1997Co-Authors: André Desbiens, André Pomerleau, K. Najim, Daniel HodouinAbstract:This paper presents practical aspects and an application of the decentralized partial state reference model adaptive control (DPSRMAC) to a Grinding Circuit. This control algorithm belongs to the class of long-range predictive controllers. Having in mind the pole placement approach, the quadratic control objective is expressed in terms of input and output tracking errors. The regulation and servo performances can be specified independently. A robust parameter estimation algorithm is used for on-line identification of the single-input/single-output (SISO) models. Simulations have been carried out using a phenomenological model of a Grinding Circuit. Comparisons are made between the DPSRMAC and decentralized SISO extended PI controllers, showing the efficiency and robustness of the adaptive control algorithm. © 1997 John Wiley & Sons, Ltd.
J. A. Herbst - One of the best experts on this subject based on the ideXlab platform.
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Optimal control of a ball mill Grinding Circuit—II. Feedback and optimal control
Chemical Engineering Science, 1991Co-Authors: Raj K. Rajamani, J. A. HerbstAbstract:Abstract Dynamic models of the pilot scale Grinding Circuit were developed and verified in Part I of this two-part paper. In particular, a detailed model and a much simplified model were discussed. Here it is shown that the two principal proportional—integral controllers on the Grinding Circuit can be tuned off-line with the use of a detailed model. Then, the simplified model, after linearization, is used in optimal control runs. The optimal controller can be used to achieve a variety of control objectives. But for on-line use the controller would need an on-line identification scheme.
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optimal control of a ball mill Grinding Circuit ii feedback and optimal control
Chemical Engineering Science, 1991Co-Authors: Raj K. Rajamani, J. A. HerbstAbstract:Abstract Dynamic models of the pilot scale Grinding Circuit were developed and verified in Part I of this two-part paper. In particular, a detailed model and a much simplified model were discussed. Here it is shown that the two principal proportional—integral controllers on the Grinding Circuit can be tuned off-line with the use of a detailed model. Then, the simplified model, after linearization, is used in optimal control runs. The optimal controller can be used to achieve a variety of control objectives. But for on-line use the controller would need an on-line identification scheme.
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Optimal control of a ball mill Grinding Circuit—I. Grinding Circuit modeling and dynamic simulation
Chemical Engineering Science, 1991Co-Authors: Raj K. Rajamani, J. A. HerbstAbstract:Abstract Mineral Grinding Circuits can be controlled with a set of proportional—integral (PI) controllers or alternatively by specialized controllers which make use of optimal control theory. The latter control strategy is superior in the sense that feed solid and water addition rates are manipulated in concert to achieve a specified control objective. A dynamic model is needed for PI control the model can be used for off-line tuning. Off-line tuning circumvents the problem of on-line tuning during which transients persist for a long time, resulting in lost production. The key elements of the full dynamic model are the population balance model of the ball mill and an empirical model of the hydrocyclone. The model development and its verification for both steady- and unsteady-state responses are shown. On-line computations with the full dynamic model require the solution 37 differential equations at every sampling instant. In addition, optimal control calculations may overburden the control computer. Therefore, a simplified model using just three state variables is shown to be adequate for dynamic predictions. In Part II the full dynamic model is used in off-line tuning and the simplified model is used in the optimal controller. Both model predictions and pilot scale ball mill Circuit responses are shown.
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optimal control of a ball mill Grinding Circuit i Grinding Circuit modeling and dynamic simulation
Chemical Engineering Science, 1991Co-Authors: Raj K. Rajamani, J. A. HerbstAbstract:Abstract Mineral Grinding Circuits can be controlled with a set of proportional—integral (PI) controllers or alternatively by specialized controllers which make use of optimal control theory. The latter control strategy is superior in the sense that feed solid and water addition rates are manipulated in concert to achieve a specified control objective. A dynamic model is needed for PI control the model can be used for off-line tuning. Off-line tuning circumvents the problem of on-line tuning during which transients persist for a long time, resulting in lost production. The key elements of the full dynamic model are the population balance model of the ball mill and an empirical model of the hydrocyclone. The model development and its verification for both steady- and unsteady-state responses are shown. On-line computations with the full dynamic model require the solution 37 differential equations at every sampling instant. In addition, optimal control calculations may overburden the control computer. Therefore, a simplified model using just three state variables is shown to be adequate for dynamic predictions. In Part II the full dynamic model is used in off-line tuning and the simplified model is used in the optimal controller. Both model predictions and pilot scale ball mill Circuit responses are shown.
Jun-yong Zhai - One of the best experts on this subject based on the ideXlab platform.
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expert system based adaptive dynamic matrix control for ball mill Grinding Circuit
Expert Systems With Applications, 2009Co-Authors: Xisong Che, Jun-yong ZhaiAbstract:Ball mill Grinding Circuit is a multiple-input multiple-output (MIMO) system characterized with couplings and nonlinearities. Stable control of Grinding Circuit is usually interrupted by great disturbances, such as ore hardness and feed particle size, etc. Conventional model predictive control usually cannot capture the nonlinearities caused by the disturbances in real practice. Multiple models based adaptive dynamic matrix control (ADMC) is proposed for the control of ball mill Grinding Circuit. The novelty of the strategy lies in that intelligent expert system is developed to identify the current ore hardness and then select a proper model for ADMC. Compared with the various nonlinear DMC strategies, the approach can synthesize and analyze as many variables and status as possible to adequately and reliably identify the process conditions, and it does not introduce additional computational complexity, which makes it readily available to the industrial practitioner. Simulation results and industrial applications demonstrate the effectiveness and practicality of this control strategy.
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Application of model predictive control in ball mill Grinding Circuit
Minerals Engineering, 2007Co-Authors: Xisong Chen, Jun-yong Zhai, Shihua Li, Qi LiAbstract:Abstract Grinding Circuit needs to be stably controlled for high recovery rate of mineral ore and significant reduction of production cost in concentrator plants. Ball mill Grinding Circuit is essentially a multi-input–multi-output (MIMO) system with strong coupling among process variables. Simplified model with multi-loop decoupled PID control usually cannot maintain a long-time stable control in real practice. The response tests between four controlled variables (namely, product particle size, mill solids concentration, sump level and circulating load) and four manipulated variables (namely, fresh ore feed rate, mill feed water flow rate, pump speed and dilution water flow rate) are carried out to construct a four-input–four-output model of Grinding Circuit. Based on this modeling, constrained model predictive control (MPC) is adopted to handle such strong coupling system and evaluated in an iron ore concentrator plant. The variables are controlled around their set-points and a long-term stable operation of the Grinding Circuit close to their optimum operating conditions is achieved. More than three years’ operation in industry demonstrates the effectiveness and practicality of this control strategy.
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Fuzzy Logic Based On-Line Efficiency Optimization Control of a Ball Mill Grinding Circuit
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Co-Authors: Xisong Chen, Jun-yong Zhai, Qi LiAbstract:Grinding Circuit must provide stable particle size distribution and should also operate in a way to maximize mill efficiency. Fuzzy logic based on-line optimization control integrated in an expert system was developed to control product particle size while enhancing mill efficiency in a ball mill Grinding Circuit. In the supervisory level, fuzzy logic control determined the optimum set-points for the controllers in the regulatory level. The whole system not only ensured a long-term stableness of particle size even ore hardness has changed but also increased the mill efficiency more than 8 percent in practical application compared with conventional control. More than half a year's industrial operation demonstrates the practicality, reliability and effectiveness of the suggested control strategy.
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FSKD (2) - Fuzzy Logic Based On-Line Efficiency Optimization Control of a Ball Mill Grinding Circuit
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Co-Authors: Xisong Chen, Jun-yong Zhai, Shu-min FeiAbstract:Grinding Circuit must provide stable particle size distribution and should also operate in a way to maximize mill efficiency. Fuzzy logic based on-line optimization control integrated in an expert system was developed to control product particle size while enhancing mill efficiency in a ball mill Grinding Circuit. In the supervisory level, fuzzy logic control determined the optimum set-points for the controllers in the regulatory level. The whole system not only ensured a long-term stableness of particle size even ore hardness has changed but also increased the mill efficiency more than 8 percent in practical application compared with conventional control. More than half a year's industrial operation demonstrates the practicality, reliability and effectiveness of the suggested control strategy.
Tianyou Chai - One of the best experts on this subject based on the ideXlab platform.
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multivariable disturbance observer based advanced feedback control design and its application to a Grinding Circuit
IEEE Transactions on Control Systems and Technology, 2014Co-Authors: Ping Zhou, Tianyou ChaiAbstract:Design of advanced feedback control (AFC) for optimal process operation has been mostly based on a hierarchical structure for many years. Since many advanced control algorithms (such as the model predictive control) do not handle disturbances directly in their design phase, it is difficult to achieve satisfactory performance in controlling complex process operations in the presence of heavy disturbances and large uncertainties. Focused on this practical challenge, in this paper we propose a novel multivariable disturbance observer (MDOB) to improve the disturbance rejection performance of conventional AFCs. The MDOB formulation is based on the approximate inversion of the multivariable generalized system, which consists of the multivariable operation process and the lower level basic feedback control system. All the stable and realizable MDOBs are characterized in terms of time delays and nonminimum phase zeros of the open-loop generalized systems. In the proposed MDOB-based AFC, the advanced feedback controller acts as a presetting controller to generate the proper pre-setpoint for the lower level basic feedback control (BFC) system such that a desired setpoint tracking is achieved. The MDOB acts as a compensator to enhance the operational performance of the process by dynamically adjusting the setpoints of the BFC according to the observed disturbances and plant uncertainties. Theoretical analysis, simulation comparisons, and experimental evaluation using a hardware-in-loop simulation platform of a Grinding Circuit are given, showing the effectiveness, validity, and advantages of the proposed approach.
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Multivariable Grinding Circuit Control: An Modifed Analytical Decoupling Control Approach within a Unity Feedback Control Structure
Advanced Materials Research, 2012Co-Authors: Ping Zhou, Yu Zhi Gao, Tianyou ChaiAbstract:Grinding Circuit (GC) of mineral processing industry is characterized by its multivariable, high interacting, time-varying parameters and large measurement delay nature. The product particle size and the circulating load of the GC are two important production indexes that directly related to performances of the subsequent beneficiation process and production rates of the overall mineral processing plant. However, they are usually difficult to be controlled effectively with conventional control strategies due to the above mentioned complex characteristics. In this paper, a modified analytical decoupling control (ADC) scheme is proposed to handle such an intricate multivariable process with large output delay. Control studies have been performed by simulation tests for setpoint tracking, disturbance rejection and robustness problems.
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Grinding Circuit control a hierarchical approach using extended 2 dof decoupling and model approximation
Powder Technology, 2011Co-Authors: Ping Zhou, Tianyou ChaiAbstract:Abstract During the operation of a Grinding Circuit (GC), the purpose of control is to ensure the final Grinding production indices (GPIs) meet prescribed technical requirements. However, due to the complex dynamic characteristics between the GPIs and the control loops, such control objectives are difficult to achieve by using existing control methods. The complexity is reflected by the existence of strong process coupling, multiple time delays, and large time variations. In this paper, a hierarchical control approach which comprises a lower-level loop control system (LLCS) and a higher-level loop setting system (HLSS) has been presented to control the complex Grinding process. The LLCS designed by the distributed PID control technique is responsible for forcing the key process variables that closely relate to the GPIs to track the given set-points. The HLSS, which mainly consists of a feedforward pre-setting controller and a feedback compensator, is used to auto-adjust the set-points of the LLCS in the presence of significant uncertainty about the plant behavior and disturbances so as to maintain good overall operation performance. To design the HLSS, an extended 2-degrees-of-freedom (2-DOF) decoupling control method is presented together with a model approximation method based on the multiple-point step response fitting technique. At last, several simulations have been performed to demonstrate the proposed control method for GC operation.
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Multivariable decoupling internal model control for Grinding Circuit
2008 American Control Conference, 2008Co-Authors: Ping Zhou, Tianyou Chai, Hong Wang, Chun-yi SuAbstract:Grinding Circuit (GC) of mineral processing industry is characterized by its multivariable, severe coupling and multiple time delay nature. The product particle size and the mill throughput of GC are the important performance indexes directly related to the performance of the subsequent process and the production rate of the overall mineral processing plant respectively. However, they are hard to control effectively with conventional control strategies due to the above complex characteristics of GC. In this paper, a multivariable decoupling internal model control (MDIMC) scheme is adopted to handle such intricate process. Control studies have been performed by simulation tests for servo, regulatory, disturbance rejection and robustness problems.
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ACC - Multivariable decoupling internal model control for Grinding Circuit
2008 American Control Conference, 2008Co-Authors: Ping Zhou, Tianyou Chai, Hong WangAbstract:Grinding Circuit (GC) of mineral processing industry is characterized by its multivariable, severe coupling and multiple time delay nature. The product particle size and the mill throughput of GC are the important performance indexes directly related to the performance of the subsequent process and the production rate of the overall mineral processing plant respectively. However, they are hard to control effectively with conventional control strategies due to the above complex characteristics of GC. In this paper, a multivariable decoupling internal model control (MDIMC) scheme is adopted to handle such intricate process. Control studies have been performed by simulation tests for servo, regulatory, disturbance rejection and robustness problems.
