An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are deri...An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.展开更多
This paper presents work on modulated signal recognition using an artificial neural network （ANN） developed using the Python programme language. The study is basically on the analysis of analog modulated signals. Fo...This paper presents work on modulated signal recognition using an artificial neural network （ANN） developed using the Python programme language. The study is basically on the analysis of analog modulated signals. Four of the best-known analog modulation types are considered namely： amplitude modulation （AM）, double sideband （DSB） modulation, single sideband （SSB） modulation and frequency modulation （FM）. Computer simulations of the four modulated signals are carried out using MATLAB. MATLAB code is used in simulating the analog signals as well as the power spectral density of each of the analog modulated signals. In achieving an accurate classification of each of the modulated signals, extensive simulations are performed for the training of the artificial neural network. The results of the study show accurate and correct performance of the developed automatic modulation recognition with average success rate above 99.5%.展开更多
Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TE...Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TENG),a flexible self-powered tactile sensor composed of micro-frustum-arrays-structured polydimethylsiloxane(PDMS)film/copper(Cu)electrodes,and poly(vinylidenefluoride-trifluoroethylene)(P(VDF-TrFE))nanofibers has been demonstrated.The TENG-based self-powered tactile sensor can generate electrical signals through the contact-separation process of two triboelectric layers under external mechanical stimuli.Due to the uniform and controllable micro-frustum-arrays structure fabricated by micro-electro-mechanical system(MEMS)process and the P(VDF-TrFE)nanofibers fabricated by electrostatic spinning,the flexible PDMS-based sensor presents high sensitivity of 2.97 V kPa^-1,stability of 40,000 cycles(no significant decay),response time of 60 ms at 1 Hz,low detection pressure of a water drop(~4 Pa,35 mg)and good linearity of 0.99231 in low pressure region.Since the PDMS film presents ultra-flexibility and excellent-biocompatibility,the sensor can be comfortably attached on human body.Furthermore,the tactile sensor can recognize various types of human body movements by the corresponding electrical signals.Therefore,the as-prepared TENGs are potential on the prospects of gesture detection,health assessment,human-machine interfaces and so on.展开更多
基金High Technology Research and Development Program me of China (No.2 0 0 1AA413 13 0 )
文摘An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.
文摘This paper presents work on modulated signal recognition using an artificial neural network （ANN） developed using the Python programme language. The study is basically on the analysis of analog modulated signals. Four of the best-known analog modulation types are considered namely： amplitude modulation （AM）, double sideband （DSB） modulation, single sideband （SSB） modulation and frequency modulation （FM）. Computer simulations of the four modulated signals are carried out using MATLAB. MATLAB code is used in simulating the analog signals as well as the power spectral density of each of the analog modulated signals. In achieving an accurate classification of each of the modulated signals, extensive simulations are performed for the training of the artificial neural network. The results of the study show accurate and correct performance of the developed automatic modulation recognition with average success rate above 99.5%.
基金financially supported by the National Natural Science Foundation of China(51605449,51675493 and51705476)the National Key R&D Program of China(2018YFF0300605)+2 种基金Shanxi “1331 Project” Key Subject Construction(1331KSC)the Applied Fundamental Research Program of Shanxi Province(201601D021070)Zhangjiakou Science and Technology Research and Development Plan of Zhangjiakou City(1811009B-10)
文摘Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TENG),a flexible self-powered tactile sensor composed of micro-frustum-arrays-structured polydimethylsiloxane(PDMS)film/copper(Cu)electrodes,and poly(vinylidenefluoride-trifluoroethylene)(P(VDF-TrFE))nanofibers has been demonstrated.The TENG-based self-powered tactile sensor can generate electrical signals through the contact-separation process of two triboelectric layers under external mechanical stimuli.Due to the uniform and controllable micro-frustum-arrays structure fabricated by micro-electro-mechanical system(MEMS)process and the P(VDF-TrFE)nanofibers fabricated by electrostatic spinning,the flexible PDMS-based sensor presents high sensitivity of 2.97 V kPa^-1,stability of 40,000 cycles(no significant decay),response time of 60 ms at 1 Hz,low detection pressure of a water drop(~4 Pa,35 mg)and good linearity of 0.99231 in low pressure region.Since the PDMS film presents ultra-flexibility and excellent-biocompatibility,the sensor can be comfortably attached on human body.Furthermore,the tactile sensor can recognize various types of human body movements by the corresponding electrical signals.Therefore,the as-prepared TENGs are potential on the prospects of gesture detection,health assessment,human-machine interfaces and so on.
