Weihua Gui

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

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Publications (185)111.49 Total impact

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    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.
    Journal of the Franklin Institute 03/2015; DOI:10.1016/j.jfranklin.2015.02.012 · 2.26 Impact Factor
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    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.
    Hydrometallurgy 11/2014; DOI:10.1016/j.hydromet.2014.11.004 · 2.22 Impact Factor
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    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.
    International Journal of Electrical Power & Energy Systems 09/2014; 60:182–189. DOI:10.1016/j.ijepes.2014.02.018 · 3.43 Impact Factor
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    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.
    Asian Journal of Control 09/2014; DOI:10.1002/asjc.955 · 1.41 Impact Factor
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    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.
    Control Engineering Practice 08/2014; 29:1–12. DOI:10.1016/j.conengprac.2014.02.021 · 1.91 Impact Factor
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    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.
    Optimal Control Applications and Methods 08/2014; DOI:10.1002/oca.2138 · 1.06 Impact Factor
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    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.
    Asian Journal of Control 05/2014; 16(3). DOI:10.1002/asjc.847 · 1.41 Impact Factor
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    ABSTRACT: In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently.
    ISA Transactions 01/2014; 53(5). DOI:10.1016/j.isatra.2013.12.018 · 2.26 Impact Factor
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    Ning Chen, Yutian Liu, Bo Liu, Weihua Gui
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    ABSTRACT: The paper considers the parametric absolute stabilization for interconnected Lurie time-delay systems with polytopic uncertainty. The concept of parametric absolute stabilization characterizes both the existence and the stability of equilibrium in the case of uncertain parameters and reference input shift. First, the existing conditions of parametric stability and the stable region are studied by the change of the uncertain parameters and reference input based on decentralized state feedback. Then, a delay-dependent absolute stability condition in parametric stabilization region for interconnected Lurie time-delay systems with polytopic uncertainties is obtained through a linear matrix inequality method. Finally, an example is given to illustrate the effectiveness of the proposed method.
    Asian Journal of Control 01/2014; 16(1). DOI:10.1002/asjc.661 · 1.41 Impact Factor
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    ABSTRACT: 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 using an optimal selection strategy. In the strategy, the industrial conditions are classified adaptively according to the system model performance, then the kinetic parameters are selected optimally by evolutionary and particle swarm optimization algorithms for different industrial conditions. Three different representative industrial data sets are used to test the effectiveness and flexibility of the proposed modeling and parameter optimal selection approach in various situations. Finally, the kinetic model is applied to the soft measurement of the practical copper removal process with underflow, and the results demonstrate that the model effectively captures the trends of the removal reactions.
    Industrial & Engineering Chemistry Research 11/2013; 52(48):17074–17086. DOI:10.1021/ie401619h · 2.24 Impact Factor
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    ABSTRACT: Concentrate grade of bauxite flotation is an important technology indicator, which has a direct effect on aluminum quality. Considering the unity, locality and inaccuracy of existing prediction methods of concentrate grade based on machine vision, a distributed machine vision system of bauxite flotation process is built in this paper, from which an integrated prediction model of concentrate grade is presented. At first, we use experimental methods to analyse image data from different flotation stages, as well as comment on the relationship between its global trends and local trends. Then taking advantage of the multiple kernels least squares support vector machine and wavelet extreme learning machine, models for prediction of concentrate grade and its residual compensation are established respectively to predict the concentrate grade through integration. Finally, validation and industrial applications show that the integrated prediction model based on distributed machine vision has a good generalization capability, which can achieve a good prediction accuracy of concentrate grade, with a relative error of less than 6%, thus laying a foundation for optimal control based on mineral grade in flotation process. (C) 2013 Published by Elsevier Ltd.
    Minerals Engineering 11/2013; 53:31-38. DOI:10.1016/j.mineng.2013.07.003 · 1.71 Impact Factor
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    ABSTRACT: As an important indicator of flotation performance, froth texture is believed to be related with operational condition in sulphur flotation process. A novel froth images classification method based on froth colour texture unit distribution is proposed to recognise different performance of sulphur flotation in real time. The froth colour texture unit number is calculated by using colour value instead of grey level value in texture unit number, and the probability density function of froth colour texture unit number is defined as colour texture distribution, which can describe the actual textual feature more completely than traditional texture description approach. As the type of the froth colour texture distribution is unknown, a nonparametric kernel estimation method based on the fixed kernel basis is proposed. It is impossible to use the traditional varying kernel basis to compare different colour texture distributions under various conditions while the proposed fixed kernel basis can overcome the difficulty. Through transforming nonparametric description into dynamic kernel weight vector, the combination of normal kernel with polynomial kernel based sparse multiple-kernel least square support vector machine classifiers are constructed to realise the performance classification. Furthermore, the kernel matrices are reduced by Schmidt orthogonalisation theory to lower the computational complexity. The industrial application results show that the accurate performance classification of sulphur flotation can be achieved by using the proposed method.
    Minerals Engineering 11/2013; 53:203-212. DOI:10.1016/j.mineng.2013.08.011 · 1.71 Impact Factor
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    ABSTRACT: Core set inconsistency always causes confusion regarding how to select the proper core set for data reduction in inconsistent decision tables. In this paper, partitions of knowledge granules are introduced to analyze this inconsistency, and it is concluded that there are only three types of effective partitions: those that focus on exact information, those that focus on exact, partial, and negative information and those that focus on exact, partial, negative, and probabilistic information. All useful core sets are calculated systematically by converting the three types of partitions to corresponding discernibility matrices. Then, we define three types of rules, positive, inexact, and confidence rules, based on the three types of partitions. Using these rules, an intelligible rule-based strategy is proposed to select the proper core set for a practical application, which resolves the confusion caused by core set inconsistency and completes the process of data reduction. Experimental analysis and industrial results demonstrate the effectiveness of the selection strategy.
    Information Sciences 08/2013; 241:138–147. DOI:10.1016/j.ins.2013.04.002 · 3.89 Impact Factor
  • Guisheng Zhai, Ning Chen, Weihua Gui
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    ABSTRACT: The design of quantised dynamic output feedback for decentralised ℋ∞ control systems is considered with multi-input and multi-output. It is assumed that a decentralised dynamic output feedback has been designed for a decentralised continuous-time LTI system, so that the closed-loop system is stable and a desired ℋ∞ disturbance attenuation level is achieved, and that each channel's measurement outputs are quantised before they are passed to the local controller. We propose a local-output-dependent strategy for updating the quantisers' parameters, so that the overall closed-loop system is asymptotically stable and achieves the same ℋ∞ disturbance attenuation level. Both the pre-designed controllers and the quantisers' parameters are constructed in a decentralised manner, depending on local measurement outputs.
    IET Control Theory and Applications 07/2013; 7(10):1408-1414. DOI:10.1049/iet-cta.2012.1029 · 1.84 Impact Factor
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    ABSTRACT: A novel froth image analysis based production condition recognition method is presented to identify the froth phases under various production conditions. Gabor wavelet transformation is employed to froth image processing firstly due to the ability of Gabor functions in simulating the response of the simple cells in the visual cortex. Successively, the statistical distribution profiles based feature parameters of the Gabor filter responses rather than the conventional mean and variance are extracted to delineate the essential statistical information of the froth images. The amplitude and phase representations of the Gabor filter responses are both taken into account by empirical marginal and joint statistical modeling. At last, a simple learning vector quantization (LVQ) neural network model is used to learn an effective classifier to recognize the froth production conditions. The effectiveness of this method is validated by the real production data on industrial scale from a bauxite dressing plant.
    International Journal of Computational Intelligence Systems 06/2013; 6(5):969-986. DOI:10.1080/18756891.2013.809938 · 0.45 Impact Factor
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    ABSTRACT: It is well accepted that the surface texture appearance of the flotation froth involves crucial information about its separation process, which can be used as an effective criterion for the qualitative assessment of the flotation performance. To obtain the distinctive characteristic of the froth surface appearance under various production conditions, a texture feature extraction method based on color co-occurrence matrix (CCM) is presented compared to the commonly used gray level co-occurrence matrix (GLCM). First, the HIS (Hue, Saturation and Intensity) color space is employed to exhibit and quantify the froth image, which yields a more intuitive description of the color properties in comparison with the RGB (Red, Green and Blue) color space. Then, the CCM is computed and the corresponding feature statistics of the froth surface texture are extracted based on the proposed matrix. Next, a new feature parameter is defined and extracted to describe the froth texture complexity based on the aforementioned texture feature statistics. After adequate offline froth images have been obtained from a bauxite flotation plant located in China under various production statuses with the corresponding concentrate grade in the froth assayed manually, the qualitative relationship between the texture complexity and the corresponding concentrate grade is investigated. Consequently, the optimal texture complexity range to achieve satisfactory production index is obtained for the further research of the optimal control of the flotation process. Experimental results have verified the effectiveness of the method and demonstrated its superiority over the previous texture feature extraction methods based on GLCM.
    Minerals Engineering 06/2013; s 46–47:60–67. DOI:10.1016/j.mineng.2013.03.024 · 1.71 Impact Factor
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    ABSTRACT: We propose and investigate a new general model of fuzzy complex network systems described by Takagi-Sugeno (T-S) fuzzy model with time-varying delays. Hybrid synchronization problem is discussed for this general T-S fuzzy complex dynamical network with nondelayed and delayed coupling between nodes. Utilizing Lyapunov-Krasovskii functional method, synchronization stability criteria for the networks are established in terms of linear matrix inequalities (LMIs). These criteria reveal the relationship between coupling matrices with time-varying delays and synchronization stability of the dynamical network. Numerical simulation is provided to illustrate the effectiveness and advantage of derived theoretical results.
    Mathematical Problems in Engineering 05/2013; 2013. DOI:10.1155/2013/384654 · 1.08 Impact Factor
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    ABSTRACT: The output PDF (probability density function) shape of surface bubble size in froth flotation is believed to be closely related to the operational statuses of reagent additions. An online operational status recognition method for quality evaluation of reagent addition is presented based on adaptive learning of the dynamic distribution features of the surface bubble size. We avoid the bubble over-segmentation problem by exploring an improved image segmentation algorithm to get the accurate bubble size statistics taking account of the local regional distribution of the image brightness value. By utilizing the kernel density estimation, we obtain the PDF and CDF (cumulative distribution function) of the bubble size statistics effectively. The distribution features of the bubble size statistics under the PDROS (pre-defined reagent operation statuses) are learned by FNC (furthest neighbor clustering), successively, the current health status of the reagent addition in the test time period is inferred by Bayesian inference according to the dynamic change of the bubble size PDFs; what is more, the statistical distribution features under PDROS are updated online according to the disturbance of the process operation conditions. This status recognition method is tested and practically applied in a copper ore beneficiation plant. The experimental results on the real production data demonstrate that this method outperforms other quasi machine vision based production condition recognition methods with much lower error recognition rate. It paves the way for the realization of an optimal control and fault diagnosis for reagent addition in the flotation process operation.
    Minerals Engineering 05/2013; 45:128-141. DOI:10.1016/j.mineng.2013.02.003 · 1.71 Impact Factor
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    ABSTRACT: Generalized traveling salesman problem (GTSP) is an extension of classical traveling salesman problem (TSP), which is a combinatorial optimization problem and an NP-hard problem. In this paper, an efficient discrete state transition algorithm (DSTA) for GTSP is proposed, where a new local search operator named \textit{K-circle}, directed by neighborhood information in space, has been introduced to DSTA to shrink search space and strengthen search ability. A novel robust update mechanism, restore in probability and risk in probability (Double R-Probability), is used in our work to escape from local minima. The proposed algorithm is tested on a set of GTSP instances. Compared with other heuristics, experimental results have demonstrated the effectiveness and strong adaptability of DSTA and also show that DSTA has better search ability than its competitors.
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    ABSTRACT: As an important indicator of flotation performance, froth texture is believed to be related to operational condition in sulphur flotation process. A novel fault detection method based on froth texture unit distribution (TUD) is proposed to recognize the fault condition of sulphur flotation in real time. The froth texture unit number is calculated based on texture spectrum, and the probability density function (PDF) of froth texture unit number is defined as texture unit distribution, which can describe the actual textual feature more accurately than the grey level dependence matrix approach. As the type of the froth TUD is unknown, a nonparametric kernel estimation method based on the fixed kernel basis is proposed, which can overcome the difficulty when comparing different TUDs under various conditions is impossible using the traditional varying kernel basis. Through transforming nonparametric description into dynamic kernel weight vectors, a principle component analysis (PCA) model is established to reduce the dimensionality of the vectors. Then a threshold criterion determined by the TQ statistic based on the PCA model is proposed to realize the performance recognition. The industrial application results show that the accurate performance recognition of froth flotation can be achieved by using the proposed method.
    Mathematical Problems in Engineering 02/2013; 2013. DOI:10.1155/2013/530349 · 1.08 Impact Factor

Publication Stats

433 Citations
111.49 Total Impact Points

Institutions

  • 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