The well-known Generalized Champagne Problem on simultaneous stabilization of linear systems is solved by using complex analysis and Blonders technique. We give a complete answer to the open problem proposed by Patel ...
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The well-known Generalized Champagne Problem on simultaneous stabilization of linear systems is solved by using complex analysis and Blonders technique. We give a complete answer to the open problem proposed by Patel et al., which automatically includes the solution to the original Champagne Problem. Based on the recent development in automated inequality-type theorem proving, a new stabilizing controller design method is established. Our numerical examples significantly improve the relevant results in the literature.
A new method and apparatus is proposed to improve the precision and reduce the cost of photoelectric encoder measurements. The method is based on highest resolution measurement and completely statistical analysis. The...
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A new method and apparatus is proposed to improve the precision and reduce the cost of photoelectric encoder measurements. The method is based on highest resolution measurement and completely statistical analysis. The system includes a stepping motor, a high precision worm reduction gear, a high speed single chip microcomputer, a low cost incremental optical electric encoder and some multi interfaces of communication protocols. The single chip microcomputer as the lower system can test and collect the optical electric encoder. The PC computer as host-computer can deal with the test data. The precision of the system can reach 18 binary digits. Results of application in practice showed that the method and apparatus is efficient and effective, the cost of the apparatus is less than the some kind of system.
The paper introduces basic types of nonconventional artificial neural units and focuses their notation and classification: namely; the notation and classification of dynamic higher-order nonlinear neural units, time-d...
The paper introduces basic types of nonconventional artificial neural units and focuses their notation and classification: namely; the notation and classification of dynamic higher-order nonlinear neural units, time-delay dynamic neural units, and time-delay higher-order nonlinear neural units is introduced. Brief introduction into the simplified parallel of higher-order nonlinear aggregating function of artificial nonconventional neural units and synaptic and somatic operation of biological neurons is made. Based on still simplified mathematical notation, it is proposed that nonlinear aggregating function of neural inputs should be understood as composition of synaptic as well as partial somatic neural operation also for static neural units. Thus it unravels novel, simplified, yet universal insight into understanding more computationally powerful neurons. The classification of nonconventional artificial neural units is founded first according to nonlinearity of aggregating function, second according to the dynamic order, third according to time-delay implementation within neural units.
A platform of the Internet-based teleoperation system with an omni-directional mobile robot which has a five DOFs robot arm is constructed. Remote control of the robot through the Internet is implemented. The system i...
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A platform of the Internet-based teleoperation system with an omni-directional mobile robot which has a five DOFs robot arm is constructed. Remote control of the robot through the Internet is implemented. The system is featured as low-cost and user interface friendly: remote users can control the robot through the Internet just by a client program in a general computer. The client computer can receive the live video and environment information measured by sensors. With the help of the remote video and the local simulation, users can easily communicate with the robot. Different modules are proposed and the implementation method of the system is presented. Related experiments are conducted to test the validity of the proposed system.
A Backlash neural network model is proposed for the systems with hysteresis nonlinearity. In order to approximate the hysteresis nonlinearity, Backlash-type operators are used as one layer of the neural network. Then,...
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A Backlash neural network model is proposed for the systems with hysteresis nonlinearity. In order to approximate the hysteresis nonlinearity, Backlash-type operators are used as one layer of the neural network. Then, the number of Backlash operators and neurons of hidden layer are gotten through simulation. Compared with the normal BP network, the results show the improvement validity of the proposed Backlash neural network model for describing the hysteresis nonlinearity.
A new conversion method for fault tree (FT) to binary decision diagram (BDD) was introduced. Firstly, FT was reduced and the reduction rule was proposed, share-node conception was introduced on the basis of FT decompo...
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A new conversion method for fault tree (FT) to binary decision diagram (BDD) was introduced. Firstly, FT was reduced and the reduction rule was proposed, share-node conception was introduced on the basis of FT decomposition, then the rules of connection of component BDD was proposed. Furthermore the route-based BDD reduction rule was proved, with which reduction can be done at the same time with BDD composition, and the route sequence and cut sets can be obtained, while computation and storage is greatly reduced during the process. Finally, the procedure of the transformation is presented. The affectivity effectiveness and practicability is thereby proved.
One problem of marriage in honey bees optimization (MBO) is that its complex computation process will limit its applications. The paper proposed an improved marriage honey bees optimization (IMBO). By randomly initial...
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One problem of marriage in honey bees optimization (MBO) is that its complex computation process will limit its applications. The paper proposed an improved marriage honey bees optimization (IMBO). By randomly initializing drones and restricting the condition of iteration, the calculation process becomes easier. The global convergence characteristic of IMBO is also proved based on the Markov chain theory. With different number of nodes, traveling salesman problem(TSP) is used to compare the IMBO with MBO and genetic algorithm(GA). Simulation results show that IMBO has better convergence performance.
Focuses on a method of parameter identification from indirect data, generated by indirect model. The indirect data are preprocessed in order to approximate the direct data generated by original model. Parameters of th...
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Focuses on a method of parameter identification from indirect data, generated by indirect model. The indirect data are preprocessed in order to approximate the direct data generated by original model. Parameters of the original model are identified from the approximate direct data. This method is employed to establish ballistic mathematical model of projectile based on firing table data. A ballistic integrated coefficient is proposed and identified by parameter identification method in order to establish ballistic mathematical model. The data used in identification are approximated by firing table data. Computation showed that the method was more precise than the simple table lookup method. Moreover, the method is a low-cost way to identify parameters and establish ballistic models.
The time series of wind power generating capacity were examined by nonlinear dynamical methods, in order to identify chaos characteristic from its random-like waveform. The analysis of modeling with low dimensions non...
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The time series of wind power generating capacity were examined by nonlinear dynamical methods, in order to identify chaos characteristic from its random-like waveform. The analysis of modeling with low dimensions nonlinear dynamics indicated that time series of wind power generation capacity have chaos characteristic, and wind power generating capacity can be predicted in short time.
In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of ro...
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ISBN:
(纸本)9623675445
In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MARS) for speed estimation are used to improve the perfornance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved perfornance in low speed range.
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