In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural...In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural network proportion-integration-differentiation （PID） control parameters on-line adjustment is utilized to improve system accuracy, celerity and stability. Simulation results indicate that with the control system proposed in this paper, the system deviation is reduced, therefore accuracy is improved; response speed for step signal and sinusoidal signal gets faster, thus acceleration is rapidly improved; and the system can be restored to the control value in case of interfering, so stability is improved.展开更多
In order to monitor the working state of piston motor and measure its instantaneous rotation speed accurately, the measuring principle and method of instantaneous rotation speed based on industrial personal computer a...In order to monitor the working state of piston motor and measure its instantaneous rotation speed accurately, the measuring principle and method of instantaneous rotation speed based on industrial personal computer and data acquisition card are introduced, and the major error source, influence mechanism and processing method of data quantization error are dis- cussed. By means of hybrid programming approach of LabVIEW and MATLAB, the instantaneous rotation speed measurement system for the piston motor in variable speed hydraulic system is designed. The simulation and experimental results show that the designed instantaneous speed measurement system is feasible. Furthermore, the sampling frequency has an important influ- ence on the instantaneous rotation speed measurement of piston motor and higher sampling frequency can lower quantization er- ror and improve measurement accuracy.展开更多
Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting ...Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.展开更多
Parts with varied curvature features play increasingly critical roles in engineering, and are often machined under high-speed continuous-path running mode to ensure the machining efficiency. However, the continuous-pa...Parts with varied curvature features play increasingly critical roles in engineering, and are often machined under high-speed continuous-path running mode to ensure the machining efficiency. However, the continuous-path running trajectory error is significant during high-feed-speed machining, which seriously restricts the machining precision for such parts with varied curvature features. In order to reduce the continuous-path running trajectory error without sacrificing the machining efficiency, a pre-compensation method for the trajectory error is proposed. Based on the formation mechanism of the continuous-path running trajectory error analyzed, this error is estimated in advance by approximating the desired toolpath with spline curves. Then, an iterative error pre-compensation method is presented. By machining with the regenerated toolpath after pre-compensation instead of the uncompensated toolpath, the continuous-path running trajectory error can be effectively decreased without the reduction of the feed speed. To demonstrate the feasibility of the proposed pre-compensation method, a heart curve toolpath that possesses varied curvature features is employed. Experimental results indicate that compared with the uncompensated processing trajectory, the maximum and average machining errors for the pre-compensated processing trajectory are reduced by 67.19% and 82.30%, respectively. An easy to implement solution for high efficiency and high precision machining of the parts with varied curvature features is provided.展开更多
Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SM...Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.展开更多
In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the...In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the guidance profile,and its convergence in the varying speed scenario is proved.A relationship between flight states,guidance input and impact speed is established.By applying the fixed-time convergence control theory of error dynamics,an impact speed corrector is built with the above guidance profile,which can implement impact speed correction without affecting the impact angle constraint.Numerical simulations with various impact speed and angle constraints are conducted to demonstrate the performance of the proposed guidance law,and the robustness is also verified by Monte Carlo tests.展开更多
Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,...Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.展开更多
This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two win...This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).展开更多
High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase...High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase-locked loop(PLL)type filters with respect to ramp speed reference tracking and steady-state performances,as well as the achievement of adaptive cutoff frequency control.An improved LPF-based filter structure with no ramping and steady-state errors caused by filter parameter quantization effects is proposed,which is suitable for applying LPF for sensorless drives of AC machines,especially when fixed-point digital signal processor is selected e.g.in mass production.Furthermore,the potential of adopting PLL for speed filtering is explored.It is demonstrated that PLL type filters can well maintain the advantages offered by the improved LPF.Moreover,it is found that the PLL type filters exhibit almost linear relationship between the cutoff frequency of the PLL filter and its proportional-integral(PI)gains,which can ease the realization of speed filters with adaptive cutoff frequency for improving the speed transient performance.The proposed filters are verified experimentally.The PLL type filter with adaptive cutoff frequency can provide satisfactory performances under various operating conditions and is therefore recommended.展开更多
Form error measurement is a critical exercise in providing measures for the quality control in the precision manufacturing industry.Coordinate measuring machine （CMM） is one of the automated systems used in the accu...Form error measurement is a critical exercise in providing measures for the quality control in the precision manufacturing industry.Coordinate measuring machine （CMM） is one of the automated systems used in the accurate and precise dimensional measurements and geometrical form.This paper aims to study the effect of dynamic original unforeseeable errors at different undulations per revolution （UPR） of standard artifact measurement using selected two types of CMM touchtriggering stylus.Stylus-type and stylus-speed parameters were adopted and utilized throughout the course of experiment.The results are analyzed using fast Fourier transformation to obtain foreseeable geometrical errors due to CMM machine structure and stylus scanning speeds.The results of experiment successfully indicate that the number of UPR plays an important role in determining the CMM accuracy level of the roundness measurement result.Some specific error equations for stylus system and machine structure responses have been postulated and analysed to empirically predict the accuracy of PRISMOBridge-CMM-type at National Institute for Standards （NIS） in egypt.展开更多
The throughput performance of modulation and coding schemes （MCS） selection with channel quality estimation errors （CQEE） is analyzed for high-speed downlink packet access （HSDPA）. To reduce the loss of throughp...The throughput performance of modulation and coding schemes （MCS） selection with channel quality estimation errors （CQEE） is analyzed for high-speed downlink packet access （HSDPA）. To reduce the loss of throughput caused by CQEE, the robust MCS selection method and adaptive MCS switching scheme are proposed. In addition, automatic repeat request （ARQ） scheme is used to improve the block error rate （BLER） performance. Simulation results show that the proposed methods decrease the throughput loss resulted from CQEE efficiently and BLER performance gets better with ARQ scheme.展开更多
文摘In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural network proportion-integration-differentiation （PID） control parameters on-line adjustment is utilized to improve system accuracy, celerity and stability. Simulation results indicate that with the control system proposed in this paper, the system deviation is reduced, therefore accuracy is improved; response speed for step signal and sinusoidal signal gets faster, thus acceleration is rapidly improved; and the system can be restored to the control value in case of interfering, so stability is improved.
基金National Natural Science Foundation of China(No.51275375,No.51509006)Shaanxi Provincial Natural Science Basic Research Plan(No.2014JQ7246)+1 种基金The Science and Technology of Hubei Province(No.B2015115)Doctoral Research Foundation of Hubei University of Automotive Technology(No.BK201403)
文摘In order to monitor the working state of piston motor and measure its instantaneous rotation speed accurately, the measuring principle and method of instantaneous rotation speed based on industrial personal computer and data acquisition card are introduced, and the major error source, influence mechanism and processing method of data quantization error are dis- cussed. By means of hybrid programming approach of LabVIEW and MATLAB, the instantaneous rotation speed measurement system for the piston motor in variable speed hydraulic system is designed. The simulation and experimental results show that the designed instantaneous speed measurement system is feasible. Furthermore, the sampling frequency has an important influ- ence on the instantaneous rotation speed measurement of piston motor and higher sampling frequency can lower quantization er- ror and improve measurement accuracy.
基金the Gansu Province Soft Scientific Research Projects(No.2015GS06516)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(No.J201304)。
文摘Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.
基金Supported by National Natural Science Foundation of China(Grant Nos.51575087,51205041)Science Fund for Creative Research Groups(Grant No.51321004)+1 种基金Basic Research Foundation of Key Laboratory of Liaoning Educational Committee,China(Grant No.LZ2014003)Research Project of Ministry of Education of China(Grant No.113018A)
文摘Parts with varied curvature features play increasingly critical roles in engineering, and are often machined under high-speed continuous-path running mode to ensure the machining efficiency. However, the continuous-path running trajectory error is significant during high-feed-speed machining, which seriously restricts the machining precision for such parts with varied curvature features. In order to reduce the continuous-path running trajectory error without sacrificing the machining efficiency, a pre-compensation method for the trajectory error is proposed. Based on the formation mechanism of the continuous-path running trajectory error analyzed, this error is estimated in advance by approximating the desired toolpath with spline curves. Then, an iterative error pre-compensation method is presented. By machining with the regenerated toolpath after pre-compensation instead of the uncompensated toolpath, the continuous-path running trajectory error can be effectively decreased without the reduction of the feed speed. To demonstrate the feasibility of the proposed pre-compensation method, a heart curve toolpath that possesses varied curvature features is employed. Experimental results indicate that compared with the uncompensated processing trajectory, the maximum and average machining errors for the pre-compensated processing trajectory are reduced by 67.19% and 82.30%, respectively. An easy to implement solution for high efficiency and high precision machining of the parts with varied curvature features is provided.
基金supported by the National Natural Science Foundation of China(No.U2142206).
文摘Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.
基金supported by the National Natural Science Foundation of China(No.52175214)。
文摘In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the guidance profile,and its convergence in the varying speed scenario is proved.A relationship between flight states,guidance input and impact speed is established.By applying the fixed-time convergence control theory of error dynamics,an impact speed corrector is built with the above guidance profile,which can implement impact speed correction without affecting the impact angle constraint.Numerical simulations with various impact speed and angle constraints are conducted to demonstrate the performance of the proposed guidance law,and the robustness is also verified by Monte Carlo tests.
基金The National Natural Science Foundation of China under contract No.41931076the National Center for Basic Sciences Project under contract No.42388102the Laoshan Laboratory under contract No.LSKJ202205100.
文摘Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.
基金National Key Research and Development Program of the Ministry of Science(2018YFB1502801)Hubei Provincial Natural Science Foundation(2022CFD017)Innovation and Development Project of China Meteorological Administration(CXFZ2023J044)。
文摘This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).
基金This work was supported in part by Lodam A/S and in part by the PSO-ELFORSK Program。
文摘High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase-locked loop(PLL)type filters with respect to ramp speed reference tracking and steady-state performances,as well as the achievement of adaptive cutoff frequency control.An improved LPF-based filter structure with no ramping and steady-state errors caused by filter parameter quantization effects is proposed,which is suitable for applying LPF for sensorless drives of AC machines,especially when fixed-point digital signal processor is selected e.g.in mass production.Furthermore,the potential of adopting PLL for speed filtering is explored.It is demonstrated that PLL type filters can well maintain the advantages offered by the improved LPF.Moreover,it is found that the PLL type filters exhibit almost linear relationship between the cutoff frequency of the PLL filter and its proportional-integral(PI)gains,which can ease the realization of speed filters with adaptive cutoff frequency for improving the speed transient performance.The proposed filters are verified experimentally.The PLL type filter with adaptive cutoff frequency can provide satisfactory performances under various operating conditions and is therefore recommended.
文摘Form error measurement is a critical exercise in providing measures for the quality control in the precision manufacturing industry.Coordinate measuring machine （CMM） is one of the automated systems used in the accurate and precise dimensional measurements and geometrical form.This paper aims to study the effect of dynamic original unforeseeable errors at different undulations per revolution （UPR） of standard artifact measurement using selected two types of CMM touchtriggering stylus.Stylus-type and stylus-speed parameters were adopted and utilized throughout the course of experiment.The results are analyzed using fast Fourier transformation to obtain foreseeable geometrical errors due to CMM machine structure and stylus scanning speeds.The results of experiment successfully indicate that the number of UPR plays an important role in determining the CMM accuracy level of the roundness measurement result.Some specific error equations for stylus system and machine structure responses have been postulated and analysed to empirically predict the accuracy of PRISMOBridge-CMM-type at National Institute for Standards （NIS） in egypt.
文摘The throughput performance of modulation and coding schemes （MCS） selection with channel quality estimation errors （CQEE） is analyzed for high-speed downlink packet access （HSDPA）. To reduce the loss of throughput caused by CQEE, the robust MCS selection method and adaptive MCS switching scheme are proposed. In addition, automatic repeat request （ARQ） scheme is used to improve the block error rate （BLER） performance. Simulation results show that the proposed methods decrease the throughput loss resulted from CQEE efficiently and BLER performance gets better with ARQ scheme.
