Network emulation environment is great importance to the research of network protocols, applications and security mechanism. Large-scale network topology generation is one of key technologies to construct network emul...
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Because it is difficult for the traditional PID algorithm for nonlinear time-variant control objects to obtain satisfactory control results, this paper studies a neuron PID controller. The neuron PID controller makes ...
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Because it is difficult for the traditional PID algorithm for nonlinear time-variant control objects to obtain satisfactory control results, this paper studies a neuron PID controller. The neuron PID controller makes use of neuron self-learning ability, complies with certain optimum indicators, and automatically adjusts the parameters of the PID controller and makes them adapt to changes in the controlled object and the input reference signals. The PID controller is used to control a nonlinear time-variant membrane structure inflation system. Results show that the neural network PID controller can adapt to the changes in system structure parameters and fast track the changes in the input signal with high control precision.
The robust D stabilization problem is considered for singular systems with polytopic uncertainties in this *** the derivative matrix E and the state matrix A are with uncertainties,which were not considered ***,with t...
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The robust D stabilization problem is considered for singular systems with polytopic uncertainties in this *** the derivative matrix E and the state matrix A are with uncertainties,which were not considered ***,with the introduction of some free matrices,a necessary and sufficient condition for the singular system to be D stable is proposed,based on which,the robust D stable problem is solved,and a sufficient condition for the closed system to be robust D stabilizable is *** desired state feedback controller is given in an explicit *** examples show the efficiency of the proposed approach.
Biological processes have produced the ultimate intelligent system, and now we are trying to understand biology by building intelligent systems. Protein Secondary structure prediction is essential for the tertiary str...
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In order to build high accuracy integral dynamic models of cold rolling mill system, by analyzing the vibration process of cold rolling, the dynamic model of 4-h mill, including the rolling process model, the mill rol...
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In order to build high accuracy integral dynamic models of cold rolling mill system, by analyzing the vibration process of cold rolling, the dynamic model of 4-h mill, including the rolling process model, the mill roll stand structure model and the hydraulic servo system model is built. These three models are coupled and linearized, then the multiple input and multiple output （MIMO） linear transfer function model of single stand 4-h cold mill system is obtained. The model with the proposed data proves its validity, meanwhile the effects of different working conditions on the stability of cold rolling mill system have been discussed. Simulation resulsts show that the model accords with former models and has its own advancement. It contributes to the further study and supression of coupling vibraiton.
To solve the problem that standard differential evolution algorithm is easy to premature convergence, here gives a new variant form-self-disturbance variation, and takes some improvement to it. New mutation could main...
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Most faults of large-scale electromechanical equipment are trendy ones, often have long course characteristics. As the fault information is usually lost in non-fault information of condition changes, the traditional m...
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ISBN:
(纸本)9784883254194
Most faults of large-scale electromechanical equipment are trendy ones, often have long course characteristics. As the fault information is usually lost in non-fault information of condition changes, the traditional methods are difficult to predict it effectively. To solve this problem, field data-based fault prediction theory and methods are studied primary for large rotating electromechanical equipment, and new nonlinear prediction way in multi-transform domains is proposed to achieve long course prediction for the equipment under variable operating conditions. In the new way fault feature extraction method of nonlinear dimensionality reduction is investigated to extract fault and potential fault sensitive information and to separate faulty development changes from non-fault energy changes. The research is important for large electromechanical equipment to achieve early fault prediction, guarantee safe operation, save maintenance costs, improve utilization and implement scientific maintenance.
When the backscattering method is adopted to test the concentration and the size of soot, it's very important to analyze the backscattering characteristics of soot to determine the optimal light source, detector a...
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In this paper, an automatic arithmetic generation system which can be remotely controlled by a particular speaker is designed and implemented to improve children's interest in learning math and facilitate parents ...
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This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
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ISBN:
(纸本)9780955529337
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
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