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Temperature compensation method of silicon microgyroscope based on BP neural network 被引量:5
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作者 夏敦柱 王寿荣 周百令 《Journal of Southeast University(English Edition)》 EI CAS 2010年第1期58-61,共4页
The temperature characteristics of a silicon microgyroscope are studied, and the temperature compensation method of the silicon microgyroscope is proposed. First, an open-loop circuit is adopted to test the entire mic... The temperature characteristics of a silicon microgyroscope are studied, and the temperature compensation method of the silicon microgyroscope is proposed. First, an open-loop circuit is adopted to test the entire microgyroscope's resonant frequency and quality factor variations over temperature, and the zero bias changing trend over temperature is measured via a closed-loop circuit. Then, in order to alleviate the temperature effects on the performance of the microgyroscope, a kind of temperature compensated method based on the error back propagation(BP)neural network is proposed. By the Matlab simulation, the optimal temperature compensation model based on the BP neural network is well trained after four steps, and the objective error of the microgyroscope's zero bias can achieve 0.001 in full temperature range. By the experiment, the real time operation results of the compensation method demonstrate that the maximum zero bias of the microgyroscope can be decreased from 12.43 to 0.75(°)/s after compensation when the ambient temperature varies from -40 to 80℃, which greatly improves the zero bias stability performance of the microgyroscope. 展开更多
关键词 silicon microgyroscope temperature characteristic error back propagation neural network temperature compensation
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Adaptive Fuzzy Neural Control of Dynamic System
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作者 赵保军 韩月秋 毛二可 《Journal of Beijing Institute of Technology》 EI CAS 1999年第2期85-89,共5页
Aim To build an adaptive fuzzy neural controller and simulate it. Methods\ Fuzzy logic and back propagation(BP) algorithm are combined to utilize their advantages while avoiding the disadvantages. Results and Conclus... Aim To build an adaptive fuzzy neural controller and simulate it. Methods\ Fuzzy logic and back propagation(BP) algorithm are combined to utilize their advantages while avoiding the disadvantages. Results and Conclusion\ Simulation results of the third order plant with disturbances and dead times show the validity of the presented controller. The presented controller can control cases that preceding controllers were unable to control. 展开更多
关键词 error back propagation fuzzy logic learning rate nonlinear time varying parameter
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Estimation and Prediction of Gas Chromatography Retention Indices of Hydrocarbons in Straight-run Gasoline by Using Artificial Neural Network and Structural Coding Method
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作者 YIN Chun sheng GUO Wei min +2 位作者 LIU Wei ZHAO Wei PAN Zhong xiao 《Chemical Research in Chinese Universities》 SCIE CAS CSCD 2001年第1期31-40,共10页
The molecular structures of hydrocarbons in straight run gasoline were numerically coded. The nonlinear quantitative relationship(QSRR) between gas chromatography(GC) retention indices of the hydrocarbons and their m... The molecular structures of hydrocarbons in straight run gasoline were numerically coded. The nonlinear quantitative relationship(QSRR) between gas chromatography(GC) retention indices of the hydrocarbons and their molecular structures were established by using an error back propagation(BP) algorithm. The GC retention indices of 150 hydrocarbons were then predicted by removing 15 compounds(as a test set) and using the 135 remained molecules as a calibration set. Through this procedure, all the compounds in the whole data set were then predicted in groups of 15 compounds. The results obtained by BP with the correlation coefficient and the standard deviation 0 993 4 and 16 54, are satisfied. 展开更多
关键词 Structural encoding GC retention index Neural network error back propagation(BP)
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