1 Im proved Digital Costas Loop Design in Spread Spectrum C om m UnlCat lon .WANG Hongbo,DENG Li,MA Zhonggui and TU Xuyan (School of Information Engineering,University of Science and Technology Beijing,Beijing 100083,...
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1 Im proved Digital Costas Loop Design in Spread Spectrum C om m UnlCat lon .WANG Hongbo,DENG Li,MA Zhonggui and TU Xuyan (School of Information Engineering,University of Science and Technology Beijing,Beijing 100083,China) (keylaboratory of advancedcontrol of Iron and Steel process(ministry of education),University of Science and Technology Bering,Beijing 1 00083,China) A bstract-Based on software radio technique.
Dear editor,In the industrial processes, timely detection of key quality variables is very important for tracking the product quality, monitoring the process status, and achieving stable and reliable control. However,...
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Dear editor,In the industrial processes, timely detection of key quality variables is very important for tracking the product quality, monitoring the process status, and achieving stable and reliable control. However, the key quality variables are difficult to measure or have obvious time delay. The process
This paper presents an algorithm for real time weld seam detection and feature extraction of butt weld, which is based on laser vision sensor installed on the end hand of welding robot. The algorithm preprocesses the ...
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ISBN:
(纸本)9781479947249
This paper presents an algorithm for real time weld seam detection and feature extraction of butt weld, which is based on laser vision sensor installed on the end hand of welding robot. The algorithm preprocesses the weld seam images captured by laser vision sensor as first step and then detects laser stripe edges thus obtains the center of laser stripe. Then a two-step method is used to extract the initial value of center point of weld seam. Finally the weld region is separated from the laser stripe center line using iterative search method, then two edge points and accurate center point of weld region together with the width of weld seam can be calculated. Experiments have shown that the algorithm proposed in this paper has good stability and accuracy, and it can meet the real-time requirements.
Aiming at the disadvantages of the standard Particle Swarm optimization (PSO), a new particle swarm optimization algorithm based on dual mutation(DDPSO) is proposed. By comparing and analyzing the results of several B...
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A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. Th...
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A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas *** reaction stage. Part of the water produced in thepyrolysis and combust!on stag.e is assumed to be involved inthe second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.
作者：
Xu, JingSun, QingEast China University of Science and Technology
Ministry of Education The Key Laboratory of Advanced Control and Optimization for Chemical Process Shanghai200237 China Shanghai University
Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China
This paper is dealt with the rotor speed tracking problem of variable-speed wind turbine systems operating under the partial load condition. Singular perturbation techniques are used to characterize the two-time-scale...
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In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa...
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In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
The hydraulic automation position control(HAPC) system for rolling mills is always difficult to design with high accuracy due to the uncertainties and other external *** a linear,low-order and optimization parameters,...
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ISBN:
(纸本)9781479900305
The hydraulic automation position control(HAPC) system for rolling mills is always difficult to design with high accuracy due to the uncertainties and other external *** a linear,low-order and optimization parameters, the high-order uncertain dynamics and unknown disturbances in plant dynamics is estimated by extended state observer(ESO). The resulting active disturbance rejection control(ADRC) is simple to use,easy to *** results show that the proposed ADRC has better robustness and adaptability than PID.
In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new...
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In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.
This paper is concerned with a delayed SIRS epidemic model with a nonlinear incidence rate. The main results are given in terms of local stability and Hopf bifurcation. Sufficient conditions for the local stability of...
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This paper is concerned with a delayed SIRS epidemic model with a nonlinear incidence rate. The main results are given in terms of local stability and Hopf bifurcation. Sufficient conditions for the local stability of the positive equilibrium and existence of Hopf bifurcation are obtained by regarding the time delay as the bifurcation parameter. Further,the properties of Hopf bifurcation such as the direction and stability are investigated by using the normal form theory and center manifold argument. Finally,some numerical simulations are presented to verify the theoretical analysis.
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