Weihua Gui

Central South University, Ch’ang-sha-shih, Hunan, China

Are you Weihua Gui?

Claim your profile

Publications (210)145.32 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: A combined fuzzy based feedforward (FBF) and bubble size distribution (BSD) based feedback reagent dosage control strategy is proposed to implement the product indices in copper roughing process. A fuzzy theory based feedforward compensator will be used to calculated the reagent dosage in advance to eliminate the influence of large disturbances according to ore grade and handling capacity. Since the bubble size is believed to be closely related to flotation performance and responds to changes in the reagent dosage, using BSD based feedback predictive control calculates the reagent dosage to stabilize the flotation running. Instead of simple statistic feature, the bubble size with non-Gaussian feature is characterized to be probability density function (PDF) by using B-spline. A multi-output least square support vector machine (MLS-SVM) based is then applied to establish a dynamical relationship between the weights of B-spline and the reagent dosage since the weights are interrelated and related to the reagent dosage. A multiple step based optimization algorithm is finally proposed to determine the reagent dosage. Experimental results can show the effectiveness of the proposed method.
    No preview · Article · Mar 2016 · Journal of Process Control
  • [Show abstract] [Hide abstract]
    ABSTRACT: A purification process is to remove impurities through a series of reactors with additives. The theoretical calculated amount of additive does not fulfill actual requirements due to variations in the reaction environment. An additive requirement ratio is thus defined to measure the disparity between theoretical calculation and actual requirements. Considering the influence of the process underlying variations, a novel ratio prediction strategy, case-based prediction with trend distribution feature (CBP-TDF), is developed. In the strategy, the trend distribution features are firstly extracted to describe the underlying variations, and an improved case-based prediction algorithm is proposed where the similarity between these features is computed based on Kullback–Leibler divergence. The proposed strategy is applied to a copper removal process of zinc hydrometallurgy. The experiments indicate the accuracy of the ratio prediction, and the industrial application shows its effectiveness in the control of the purification process.
    No preview · Article · Jan 2016 · Control Engineering Practice

  • No preview · Article · Jan 2016 · IET Control Theory and Applications
  • [Show abstract] [Hide abstract]
    ABSTRACT: Due to the merits of sinusoidal input currents and excellent conversion efficiency, buck-type active third-harmonic injection converters have received increasing attention in recent years. However, three major problems of these converters still exist in theory and practice. First, the existence of the dc-link capacitor, utilized by early researchers, causes inrush transient and distorts the input currents. Second, in some specific situations, such as wind energy conversion system and flexible ac transmission system, these converters' capabilities of generating input reactive power need sufficient improvements. Third, proper selection of the third-harmonic injection inductor is the key challenge to implement these converters, since the inductor affects not only the current ripple but also the tracking performance of the third-harmonic current. To solve these problems, this paper studies the two-stage matrix converter with third harmonics injection and demonstrates that the dc-link capacitor can be removed by bidirectional implementation and proper control of the rectifier. Then, an algorithm enhancing the input reactive power capability is developed. Thus, sinusoidal input currents are achieved and the reactive power control range is extended significantly. Moreover, the design criteria of the third-harmonic injection inductor are discussed. Finally, the proposed method is verified by simulation and experimental results.
    No preview · Article · Jan 2016 · IEEE Transactions on Power Electronics
  • Source
    Bei Sun · Chunhua Yang · Weihua Gui
    [Show abstract] [Hide abstract]
    ABSTRACT: Nonferrous metallurgical processes are featured by their complex nature. Control of nonferrous metallurgical processes is non-trivial and related to multiple disciplines. An example is presented to illustrate the basic procedure of nonferrous metallurgical process control. A feasible way to construct a unified control approach and the potential developments of nonferrous metallurgical process control are discussed.
    Preview · Article · Dec 2015
  • [Show abstract] [Hide abstract]
    ABSTRACT: To resolve the overlapping linear sweep voltammetric peaks (LSVPs) in the case of small signals overlapping to a very big one, a parameter optimization method based on state-transition-algorithm (STA) is investigated. First, four special state transformation operators of STA are introduced and a parameter optimization method is proposed. Then, the overlapping LSVPs are obtained by simultaneously determining trace amounts of Cd2 + and Co2 + in the presence of a high concentration of Zn2 + based on optimized reagents. Finally, overlapping LSVPs are resolved into independent sub-peaks using the proposed method. The resolution results show that the goodness-of-fit of fitting curve in describing the overlapping LSVPs is more than 97%. It indicates that the proposed method is reasonable and effective for the resolution of overlapping LSVPs in the case of high signal ratio which is more than 50.
    No preview · Article · Dec 2015 · Chemometrics and Intelligent Laboratory Systems
  • Source
    Yuqian Guo · Pan Wang · Weihua Gui · Chunhua Yang
    [Show abstract] [Hide abstract]
    ABSTRACT: This study addresses the set stability of Boolean networks (BNs) and set stabilization of Boolean control networks (BCNs). Set stability determines whether a BN converges to a given subset, whereas set stabilizability addresses the issue of whether a BCN can be stabilized to a given subset. Many problems can be viewed as special cases of set stability and set stabilization, including synchronization, partial stability, and partial stabilization problems. The concepts of invariant subset and control invariant subset are introduced. Then, algorithms for the largest invariant subset and the largest control invariant subset contained in a given subset are proposed. Based on the invariant subsets obtained, the necessary and sufficient conditions for set stability and set stabilizability are established, and formulae are provided to calculate the shortest transient periods for respective initial states. A design procedure is proposed for finding all the time-optimal set stabilizers. Finally, an example is used to show the application of the proposed results to the synchronization problem of BNs.
    Full-text · Article · Nov 2015 · Automatica
  • Bei Sun · Weihua Gui · Yalin Wang · Chunhua Yang · Mingfang He
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a two-layer control scheme to address the difficulties in the modeling and control of solution purification process. Two concepts are extracted from the characteristics of solution purification process: additive utilization efficiency (AUE) and impurity removal ratio (IRR). The idea of gradient optimization of solution purification process, which transforms the economical optimization problem of solution purification process into finding an optimal decline gradient of the impurity ion concentration along the reactors, is proposed. A robust adaptive controller is designed to track the optimized impurity ion concentration in the presence of process uncertainties, disturbance and saturation. Oxidation reduction potential (ORP), which is a significant parameter of solution purification process, is also used in the scheme. The ability of the gradient optimization scheme is illustrated with a simulated case study of a cobalt removal process.
    No preview · Article · Nov 2015 · Control Engineering Practice
  • [Show abstract] [Hide abstract]
    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.
    No preview · Article · Sep 2015
  • Source
    Xiaoli Wang · Yalin Wang · Chunhua Yang · Degang Xu · Weihua Gui
    [Show abstract] [Hide abstract]
    ABSTRACT: An industrial grinding-classification process of diasporic bauxite is modeled based on the integration of phenomenological and statistical learning methods. The breakage characteristics of the ore and running status of the whole process are first investigated by laboratory testing and process sampling, respectively. Based on the population balance model (PBM) framework, the breakage distribution function is estimated from laboratory test data. The breakage rates are back-calculated directly from the industrial data, where a nonlinear breakage rate function is proposed for coarse particles. They are then correlated to the operating variables (including the water flow rate and feed flow rate), ball characteristics and material properties using the least squares support vector machine (LSSVM) method so that the model is suitable to various grinding conditions. Material transportation through the mill was treated as two equal smaller fully mixed reactors followed by a large one. The particle size distribution (PSD) of the mill product is then predicted by sequentially solving the reactors in series, considering the nonlinear breakage kinetics. A spiral classifier model is obtained with the Rosin–Rammer curve, where the bypass, real classification effect and operating conditions are included. The simulation results of the whole process by using the sequential module approach (SMA) demonstrate reasonable agreement between the predicted and measured industrial process data. The models are finally applied to the process for the prediction of particle size indices and to provide valuable information for the operation and further optimization of the process.
    Full-text · Article · Jul 2015 · Powder Technology
  • Ling Shen · Jianjun He · Chunhua Yang · Weihua Gui · Honglei Xu
    [Show abstract] [Hide abstract]
    ABSTRACT: The thermal treatment of aluminum alloy workpieces requires strict temperature uniformity in large-scale vertical quench furnaces. To achieve the desired temperature uniformity in a large-scale spatial setting, a temperature uniformity control strategy combining workpiece temperature compensation and intelligent proportional-integral-derivative (PID) decoupling control is presented. The temperature compensation of the workpiece is realized by establishing an air heat conduction model. Moreover, an intelligent PID decoupling control system based on a novel self-growing radial basis function neural network (SGRBFNN) is developed to eliminate the strong coupling effects of multiheating zones. SGRBFNN, with the structure being dynamically adjusted by a hybrid semifuzzy Gustafson-Kessel clustering algorithm, is proposed to realize the online tuning of the parameters of the PID controller. Both the simulation and industrial experiment results demonstrate that the proposed temperature control system can effectively achieve smooth regulations and significantly improve temperature uniformity. The application also demonstrates the validity and better control performance of the proposed system compared with conventional control systems.
    No preview · Article · Apr 2015 · IEEE Transactions on Control Systems Technology
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: To investigate the energy consumption involved in an event based control scheme, the problem of event based guaranteed cost consensus for distributed multi-agent systems with general linear time invariant dynamics is considered in this paper. A delay system method is used to transform the multi-agent systems into a special delay system based on a sampled-data event triggering mechanism, which only requires supervision of system states at discrete instants. Sufficient conditions to achieve the consensus with guaranteed cost are presented and expressed as a continuous constrained optimization problem with a linear objective function, linear and bilinear matrix inequalities constraints, involving the co-design of the controller gain matrix and event triggering parameters. An illustrative example is given to show the effectiveness of the proposed approach.
    Full-text · Article · Mar 2015 · Journal of the Franklin Institute
  • [Show abstract] [Hide abstract]
    ABSTRACT: Iron precipitation by goethite plays an important role in zinc hydrometallurgy. The ferrous ion concentration, which is a key index for assessing the iron removal rate and process control results, cannot be measured on-line. In this study, an integrated predictive model of the ferrous ion concentration is established by integrating the mechanism model and error compensation model, which is based on data identification. The mechanism model is proposed based on an analysis of the process reaction and considering the reaction unit as a continuous stirred tank reactor model. For unknown parameters in the mechanism model, a double-particle swarm optimization algorithm based on information exchange and dynamic adjustment of the feasible region is developed for optimal selection. To improve the adaptive capability of the integrated model, we propose a model-updating strategy and parameter calibration method based on a sensitivity analysis to accomplish on-line adaptive updating of the predictive model. The simulation results demonstrate that the proposed model can effectively track the variation tendency of the ferrous ion concentration and successfully improve the adaptability of the integrated model.
    No preview · Article · Nov 2014 · Hydrometallurgy
  • [Show abstract] [Hide abstract]
    ABSTRACT: In the context of liberalized markets, market outcomes generally result from the strategic interactions of all market players. Generation company (Genco), as the distributed players, build their subjective demand evaluations (SDFs) about market for optimal bidding purpose. Due to the differences in terms of data availability and modeling techniques, subjective demand models held by various Gencos are heterogeneous and normally deviate from the real market model as well. The picture of a real electricity market game in Genco’s eye is ‘playing is believing’. Therefore, a question naturally comes to the table: how those SDFs with the heterogeneous manner impact individual player’s decision and game results. To answer this question, this paper relaxes a conventional assumption, commonly used in the classical oligopolistic equilibrium model, that one correct and uniform demand knowledge is shared by all Gencos. The results suggest that the system equilibriums would be influenced by the Gencos’ knowledge about market demand. The economic value of demand information is assessed regarding the system performances.
    No preview · Article · Sep 2014 · International Journal of Electrical Power & Energy Systems
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper studies the analysis of parametric stability and decentralized state feedback control of a kind of quantized interconnected systems. The output of each controller is quantized logarithmically before it is input to the subsystem, and the quantized density would affect the stability of the systems. First, a decentralized state feedback controller is designed for interconnected systems without quantization and the corresponding stable region is obtained. Second, for a given controller, the lower bound of the quantization density is evaluated from parameters of local controllers. Finally, the proposed method is applied to coupled inverted pendulums systems which can be viewed as quantized interconnected systems. The simulation results show that by using the proposed quantized controllers, the interconnected inverted pendulum systems are parametrically stabilized.
    No preview · Article · Sep 2014 · Asian Journal of Control
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this study, the guaranteed cost control of discrete time uncertain system with both state and input delays is considered. Sufficient conditions for the existence of a memoryless state feedback guaranteed cost control law are given in the bilinear matrix inequality form, which needs much less auxiliary matrix variables and storage space. Furthermore, the design of guaranteed cost controller is reformulated as an optimization problem with a linear objective function, bilinear, and linear matrix inequalities constraints. A nonlinear semi-definite optimization solver—PENLAB is used as a solution technique. A numerical example is given to demonstrate the effectiveness of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.
    No preview · Article · Aug 2014 · Optimal Control Applications and Methods
  • [Show abstract] [Hide abstract]
    ABSTRACT: As an effective measurement indicator of bubble stability, bubble size structure is believed to be closely related to flotation performance in copper roughing flotation. Moreover, reagent dosage has a very important influence on bubble size structure. In this paper, a novel reagent dosage predictive control method based on probability density function (PDF) of bubble size is proposed to implement the indices of roughing circuit. Firstly, the froth images captured in the copper roughing are segmented by using a two-pass watershed algorithm. In order to characterize bubble size structure with non-Gaussian feature, an entropy based B-spline estimator is hence investigated to depict the PDF of the bubble size. Since the weights of B-spline are interrelated and related to the reagent dosage, a multi-output least square support vector machine (MLS-SVM) is applied to depict a dynamic relationship between the weights and the reagent dosage. Finally, an entropy based optimization algorithm is proposed to determine reagent dosage in order to implement tracking control for the PDF of the output bubble size. Experimental results can show the effectiveness of the proposed method.
    No preview · Article · Aug 2014 · Control Engineering Practice

  • No preview · Conference Paper · Jul 2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: In flotation processes, concentrate grade is the key production index but is difficult to be measured online. The mechanism models reflect the basic tendency of concentrate grade changes but cannot provide adequate prediction precision. The data-driven models based on froth image features provide accurate prediction within well-sampled space but rely heavily on sample data with less generalization capability. So, a hybrid intelligent model combining the two kinds of model is proposed in this paper. Since the information of image features is enormous, and the relationship between image features and concentrate grade is nonlinear, a B-spline partial least squares (BS-PLS) method is adopted to construct the data-driven model for concentrate grade prediction. In order to gain better generalization capability and prediction accuracy, information entropy is introduced to integrate the mechanism model and the BS-PLS model together and modify the model output online through an output deviation compensation strategy. Moreover, a slide window scheme is employed to update the hybrid model in order to improve its adaptability. The industrial practical data testing results show that the performance of the hybrid model is better than either of the two single models and it satisfies the accuracy and stability requirements in industrial applications.
    No preview · Article · Jun 2014 · Abstract and Applied Analysis
  • [Show abstract] [Hide abstract]
    ABSTRACT: As an effective measurement of bubble stability, bubble size structure is believed to be closely related to flotation performance. Reagent dosage has a very important influence on bubble size. A novel probability density function (PDF) of bubble size based reagent dosage control method is proposed in the paper. First, froth images acquired by camera with big and tiny blobs are segmented by use of an improved two-pass watershed algorithm. With non-Gaussian features, the PDF of the bubble size is hence approximated by the estimator based on B-spline such that the PDF of the bubble size is characterized by a weight vector of the B-spline. Finally, a PDF-based reagent dosage control algorithm is proposed to make the output PDF track the given PDF according to the linear matrix inequality technique, which is established to solve its stability condition by Lyapunov stability analysis. Experimental results show the effectiveness of the proposed method.
    No preview · Article · May 2014 · Asian Journal of Control

Publication Stats

776 Citations
145.32 Total Impact Points


  • 2002-2015
    • Central South University
      • School of Information Science and Engineering
      Ch’ang-sha-shih, Hunan, China
  • 2007
    • Shaoguan University
      Chao-kuan, Guangdong, China
  • 2006
    • CSR Zhuzhou Electric Locomotive Research Institute
      Chu-chou-shih, Hunan, China
    • South Central College
      Central, Louisiana, United States
  • 1994-2000
    • Central South University of Forestry and Technology
      Ch’ang-sha-shih, Hunan, China