A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies t...A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.展开更多
The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.Howeve...The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.However,except for the channel length,different on-body loca-tions of the transmitter and receiver also influence the power supply performance.This paper fo-cuses on the wrist-to-forehead path to show the potential of BC-WPT for the brain bioelectronics such as the brain computer interface device.The channel characteristics from 10 MHz to 60 MHz are measured by a vector network analyzer(VNA)and a prototype BC-WPT system with differ-ent copper electrodes and the lowest power loss locates between-22 dB and-33 dB.Furthermore,the minimum path loss limit is simulated in Advanced Design System(ADS)software and the low-est optimum path loss can reach nearly-13 dB.Finally,a rectifier circuit is also built at the receiv-er side to harvest d.c.voltage.The results show that the open-circuit voltage(OCV)can reach 1.75 V with the transmitter of 50Ωoutput impedance supplying 5V_(pp)sine voltage at 60 MHz when adopt-ing 1 cm-diameter circular electrodes.展开更多
文摘A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.
文摘The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.However,except for the channel length,different on-body loca-tions of the transmitter and receiver also influence the power supply performance.This paper fo-cuses on the wrist-to-forehead path to show the potential of BC-WPT for the brain bioelectronics such as the brain computer interface device.The channel characteristics from 10 MHz to 60 MHz are measured by a vector network analyzer(VNA)and a prototype BC-WPT system with differ-ent copper electrodes and the lowest power loss locates between-22 dB and-33 dB.Furthermore,the minimum path loss limit is simulated in Advanced Design System(ADS)software and the low-est optimum path loss can reach nearly-13 dB.Finally,a rectifier circuit is also built at the receiv-er side to harvest d.c.voltage.The results show that the open-circuit voltage(OCV)can reach 1.75 V with the transmitter of 50Ωoutput impedance supplying 5V_(pp)sine voltage at 60 MHz when adopt-ing 1 cm-diameter circular electrodes.
