The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions....
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The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions. How to reduce carbon consumption while ensuring the quality and yield of sinter ore are the problems to be solved urgently. In this paper,An intelligentcontrol scheme for burn-through point(BTP) to carbon efficiency optimization in iron ore sintering process is presented. The comprehensive coke ratio is employed as a measure of carbon efficiency;and the BTP, a measure of the stability of the sintering process. First, a model is established to predict the comprehensive coke ratio using a back propagation neural network, and the carbon efficiency is optimized using the particle swarm optimization algorithm. This yields an optimal strand velocity. Then, the control of the BTP is taken into consideration using an expert-fuzzy control strategy. This yields another strand velocity. Finally, these two kinds of strand velocity are integrated using the fuzzy satisfaction method to produce a control input for the strand velocity. It not only improves the carbon efficiency, but also ensures the stable running of the sintering process. Part of the strategy was tested in an actual plant, and the results show the effectiveness of the scheme.
This paper investigates the issue for stability of linear system with time-varying ***,by combining the Freematrix technique and the B-L inequality,a new inequality named Free-matrix Legendre inequality is ***,based o...
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This paper investigates the issue for stability of linear system with time-varying ***,by combining the Freematrix technique and the B-L inequality,a new inequality named Free-matrix Legendre inequality is ***,based on this inequality,two sets of stability criteria are developed which are less conservative than the existing ones due to the fact that more freedom are ***,a numerical example is given to illustrate the advantage of our method.
Due to the fact that material properties may change, weighing and feeding process is difficult to achieve high accuracy with conventional control methods. This paper discusses application of iterative learning control...
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Due to the fact that material properties may change, weighing and feeding process is difficult to achieve high accuracy with conventional control methods. This paper discusses application of iterative learning control in weighing and feeding process,which takes advantage of previous control information. First, a continual state-space model is established based on dynamic analysis of weighing and feeding process. Next, this model is discretized into a two-dimensional state space model, which takes into account more state information about the process. Then, an iterative learning controller is presented, which improves the tracking performance with the increase of feeding times. A multi-objective simulated annealing is used to find the controller parameters with better control performance under the stability condition. Finally, simulation results are given, which show that a faster feed rate and more accurate feed accuracy is obtained after several feeding batches.
This paper investigates the mean square and almost sure stability of a class of neutral stochastic differential delay equations with highly nonlinear *** first examine the regularity of the solution to the highly nonl...
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This paper investigates the mean square and almost sure stability of a class of neutral stochastic differential delay equations with highly nonlinear *** first examine the regularity of the solution to the highly nonlinear neutral stochastic differential delay *** the explicit stability conditions are obtained by the Lyapunov functional and semimartingale convergence ***,the explicit stability conditions of pure delay neutral stochastic differential delay equations are *** is revealed that the delay term in the drift can contribute to the mean square and almost sure stability.
In order to improve the utilization of carbon in a sintering process, it is necessary to predict and optimize carbon efficiency. In the paper, first, comprehensive coke ratio(CCR) is taken to be a metric of the carb...
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In order to improve the utilization of carbon in a sintering process, it is necessary to predict and optimize carbon efficiency. In the paper, first, comprehensive coke ratio(CCR) is taken to be a metric of the carbon efficiency. By analyzing the sintering mechanism, sintering parameters affecting the CCR are determined. Next, the fuzzy C-means clustering algorithm is used to identify different operating conditions. Then, least-squares support vector machine(LS-SVM) sub-models are established for the different operating conditions, and a CCR prediction model is established by incorporating the sub-models using the TS fuzzy intelligent fusion method. Finally, based on the CCR prediction model, a differential evolution algorithm is used to optimize the CCR by adjusting the operating parameters. Simulations using actual run data show that the prediction accuracy of the CCR prediction model is higher than that of a back-propagation neural network model and a single LS-SVM model, and the carbon efficiency optimization strategy reduced the CCR by 1.97 kg/t on average. Thus, the method provides us a guidance for an actual sintering process.
In this paper, a fractional-order gene regulatory network model with two delays is investigated. The existence condition of Hopf bifurcation is deduced by analyzing its characteristic equation, where the total delay i...
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In this paper, a fractional-order gene regulatory network model with two delays is investigated. The existence condition of Hopf bifurcation is deduced by analyzing its characteristic equation, where the total delay is taken as a bifurcation parameter. These bifurcation behaviors may cause the network system heavy oscillation and instability. An fractional PD control method is proposed to control bifurcations in the system. Finally, numerical simulations are provided to verify the theoretical analysis. Simulation results show that the nonlinear behavior of the system can be controlled by this method.
In this paper, bifurcation analysis and control of fractional-order quorum sensing network regulated by s RNA is studied. The dynamics of fractional quorum sensing network with time-delay is analyzed. The stability cr...
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In this paper, bifurcation analysis and control of fractional-order quorum sensing network regulated by s RNA is studied. The dynamics of fractional quorum sensing network with time-delay is analyzed. The stability criterion and bifurcation conditions of the fractional quorum sensing network are given. In order to control the dynamic properties of fractional order systems, a feedback controller is designed, and the complex dynamics of controlled fractional-order networks are further investigated. The simulation results show that this control method can achieve the ideal control effect.
The relationship of state parameters and burden distribution is uncertain in blast furnaces. In the present industry,burden operation mainly relies on the experiences of the workers. So it is difficult to control burd...
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The relationship of state parameters and burden distribution is uncertain in blast furnaces. In the present industry,burden operation mainly relies on the experiences of the workers. So it is difficult to control burden operation. To solve these problems, this paper presents a model to adjust the burden distribution using fuzzy C-means(FCM) and wavelet analysis. First,multiple condition states of blast furnaces are analysed through data processing, the state parameters are clustered based on the similarity, and then this paper searches for the corresponding burden parameters from the history data. Finally, for different state clusters, best burden parameters are selected to adjust the conditions. Simulation results show that the burden distribution adjustments based on the state parameters clustering are efficient.
Cooperative monitoring targets of mobile robots is of great importance in military, civil, and medical applications. In order to achieve multi-robot coordinated monitoring, this paper proposes a new distributed path p...
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In this paper, we study two-player evolutionary prisoner's dilemma on regular graphs and identify the stochastically stable equilibria for infinite populations. We consider four different update rules: Birth-death...
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