Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace(BF).However, due to the low transparency of this process, operators adjust the burden distribution according...
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Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace(BF).However, due to the low transparency of this process, operators adjust the burden distribution according to their own experiences,which makes it difficult to keep optimal production indexes for a BF. In this paper, an intelligent selection strategy of burden distribution is devised according to the energy-consuming index, where carbon-monoxide utilization rate(CMUR) is taken as the energy-consuming index. First, state variables are chosen based on the calculated Pearson correlation coefficient among each state variable. Then, the chosen state variables are divided into five clusters by k-means clustering algorithm. Finally, the values of CMUR in each condition cluster with different burden distribution are counted. According to the statistics, the burden distribution with the highest CMUR is judged to be the optimal one. Simulation results based on industrial data show that the proposed strategy selects the optimal burden distribution and provides a reasonable guide for the operators.
This paper investigates the stabinzability of positive time-deray system,The nonnegative constraint makes the design of a control law different from a general ***,a method to calculate the L gain of a positive time-de...
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This paper investigates the stabinzability of positive time-deray system,The nonnegative constraint makes the design of a control law different from a general ***,a method to calculate the L gain of a positive time-delay system is ***,the design of a state feedback controller and a high-gain observer is presented by taking full advantage of the characteristics of the positiveness of the ***,the observer and feedback controller are combined to stabilize the system and improve dynamic performance.A numerical example illustrates the provided method is effective.
Aiming at the problem that the process of gesture recognition based on color image is greatly affected by environmental factors such as lighting, a gesture intent understanding method based on the fusion of Red-Green-...
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Aiming at the problem that the process of gesture recognition based on color image is greatly affected by environmental factors such as lighting, a gesture intent understanding method based on the fusion of Red-Green-Blue(RGB) data and depth data is proposed. Firstly, the gesture feature extraction based on the Speeded Up Robust Feature(SURF) method after foreground segmentation are used to get gesture information. Then, we apply Backpropagation(BP) neural network to classify and recognize gestures. The final recognition results are obtained through data fusion from recognition results based on both RGB images and depth images. We evaluated the effectiveness of the proposed method through Cha Learn Gesture Database.
To meet the needs of high speed and good environmental adaptability for data transmission in industrial robot servo systems, this paper presents a wireless transmission technology on a data acquisition control termina...
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To meet the needs of high speed and good environmental adaptability for data transmission in industrial robot servo systems, this paper presents a wireless transmission technology on a data acquisition control terminal. The system is based on STM32 F103 RET6 processor and reads cache data from the SRAM of FPGA in DMA method, and communicates with a WIFI chip, Marvell 88 w8686, through the SDIO interface. A host computer segments and filters the data received by the WIFI chip and sends control commands back to STM32. The functions of the hardware and software of the system contains data compression and storage, wireless data transmission, data display, and control-command transmission. An experimental platform has been built. It carries out real-time transmission of 8-16 digits based on the TCP/IP protocol with expected performance.
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.
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.
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 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.
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.
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.
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