Compensation for positioning error of industrial robot for flexible vision measuring system

Science.gov (United States)

Guo, Lei; Liang, Yajun; Song, Jincheng; Sun, Zengyu; Zhu, Jigui

2013-01-01

Positioning error of robot is a main factor of accuracy of flexible coordinate measuring system which consists of universal industrial robot and visual sensor. Present compensation methods for positioning error based on kinematic model of robot have a significant limitation that it isn't effective in the whole measuring space. A new compensation method for positioning error of robot based on vision measuring technique is presented. One approach is setting global control points in measured field and attaching an orientation camera to vision sensor. Then global control points are measured by orientation camera to calculate the transformation relation from the current position of sensor system to global coordinate system and positioning error of robot is compensated. Another approach is setting control points on vision sensor and two large field cameras behind the sensor. Then the three dimensional coordinates of control points are measured and the pose and position of sensor is calculated real-timely. Experiment result shows the RMS of spatial positioning is 3.422mm by single camera and 0.031mm by dual cameras. Conclusion is arithmetic of single camera method needs to be improved for higher accuracy and accuracy of dual cameras method is applicable.

The Neural-fuzzy Thermal Error Compensation Controller on CNC Machining Center

Science.gov (United States)

Tseng, Pai-Chung; Chen, Shen-Len

The geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80µm to 3µm. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from ±10µm to ±3µm.

US-LHC IR magnet error analysis and compensation

International Nuclear Information System (INIS)

Wei, J.; Ptitsin, V.; Pilat, F.; Tepikian, S.; Gelfand, N.; Wan, W.; Holt, J.

1998-01-01

This paper studies the impact of the insertion-region (IR) magnet field errors on LHC collision performance. Compensation schemes including magnet orientation optimization, body-end compensation, tuning shims, and local nonlinear correction are shown to be highly effective

Poster - 49: Assessment of Synchrony respiratory compensation error for CyberKnife liver treatment

International Nuclear Information System (INIS)

Liu, Ming; Cygler, Joanna; Vandervoort, Eric

2016-01-01

The goal of this work is to quantify respiratory motion compensation errors for liver tumor patients treated by the CyberKnife system with Synchrony tracking, to identify patients with the smallest tracking errors and to eventually help coach patient’s breathing patterns to minimize dose delivery errors. The accuracy of CyberKnife Synchrony respiratory motion compensation was assessed for 37 patients treated for liver lesions by analyzing data from system logfiles. A predictive model is used to modulate the direction of individual beams during dose delivery based on the positions of internally implanted fiducials determined using an orthogonal x-ray imaging system and the current location of LED external markers. For each x-ray pair acquired, system logfiles report the prediction error, the difference between the measured and predicted fiducial positions, and the delivery error, which is an estimate of the statistical error in the model overcoming the latency between x-ray acquisition and robotic repositioning. The total error was calculated at the time of each x-ray pair, for the number of treatment fractions and the number of patients, giving the average respiratory motion compensation error in three dimensions. The 99 th percentile for the total radial error is 3.85 mm, with the highest contribution of 2.79 mm in superior/inferior (S/I) direction. The absolute mean compensation error is 1.78 mm radially with a 1.27 mm contribution in the S/I direction. Regions of high total error may provide insight into features predicting groups of patients with larger or smaller total errors.

Poster - 49: Assessment of Synchrony respiratory compensation error for CyberKnife liver treatment

Energy Technology Data Exchange (ETDEWEB)

Liu, Ming [Carleton University (Canada); Cygler, Joanna [The Ottawa Hospital Cancer Centre, Carleton University, Ottawa University (Canada); Vandervoort, Eric [The Ottawa Hospital Cancer Centre, Ottawa University (Canada)

2016-08-15

The goal of this work is to quantify respiratory motion compensation errors for liver tumor patients treated by the CyberKnife system with Synchrony tracking, to identify patients with the smallest tracking errors and to eventually help coach patient’s breathing patterns to minimize dose delivery errors. The accuracy of CyberKnife Synchrony respiratory motion compensation was assessed for 37 patients treated for liver lesions by analyzing data from system logfiles. A predictive model is used to modulate the direction of individual beams during dose delivery based on the positions of internally implanted fiducials determined using an orthogonal x-ray imaging system and the current location of LED external markers. For each x-ray pair acquired, system logfiles report the prediction error, the difference between the measured and predicted fiducial positions, and the delivery error, which is an estimate of the statistical error in the model overcoming the latency between x-ray acquisition and robotic repositioning. The total error was calculated at the time of each x-ray pair, for the number of treatment fractions and the number of patients, giving the average respiratory motion compensation error in three dimensions. The 99{sup th} percentile for the total radial error is 3.85 mm, with the highest contribution of 2.79 mm in superior/inferior (S/I) direction. The absolute mean compensation error is 1.78 mm radially with a 1.27 mm contribution in the S/I direction. Regions of high total error may provide insight into features predicting groups of patients with larger or smaller total errors.

Compensating for Channel Fading in DS-CDMA Communication Systems Employing ICA Neural Network Detectors

Directory of Open Access Journals (Sweden)

David Overbye

2005-06-01

Full Text Available In this paper we examine the impact of channel fading on the bit error rate of a DS-CDMA communication system. The system employs detectors that incorporate neural networks effecting methods of independent component analysis (ICA, subspace estimation of channel noise, and Hopfield type neural networks. The Rayleigh fading channel model is used. When employed in a Rayleigh fading environment, the ICA neural network detectors that give superior performance in a flat fading channel did not retain this superior performance. We then present a new method of compensating for channel fading based on the incorporation of priors in the ICA neural network learning algorithms. When the ICA neural network detectors were compensated using the incorporation of priors, they give significantly better performance than the traditional detectors and the uncompensated ICA detectors. Keywords: CDMA, Multi-user Detection, Rayleigh Fading, Multipath Detection, Independent Component Analysis, Prior Probability Hebbian Learning, Natural Gradient

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

Science.gov (United States)

Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

2017-12-01

We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

An IMU-Aided Body-Shadowing Error Compensation Method for Indoor Bluetooth Positioning

Directory of Open Access Journals (Sweden)

Zhongliang Deng

2018-01-01

Full Text Available Research on indoor positioning technologies has recently become a hotspot because of the huge social and economic potential of indoor location-based services (ILBS. Wireless positioning signals have a considerable attenuation in received signal strength (RSS when transmitting through human bodies, which would cause significant ranging and positioning errors in RSS-based systems. This paper mainly focuses on the body-shadowing impairment of RSS-based ranging and positioning, and derives a mathematical expression of the relation between the body-shadowing effect and the positioning error. In addition, an inertial measurement unit-aided (IMU-aided body-shadowing detection strategy is designed, and an error compensation model is established to mitigate the effect of body-shadowing. A Bluetooth positioning algorithm with body-shadowing error compensation (BP-BEC is then proposed to improve both the positioning accuracy and the robustness in indoor body-shadowing environments. Experiments are conducted in two indoor test beds, and the performance of both the BP-BEC algorithm and the algorithms without body-shadowing error compensation (named no-BEC is evaluated. The results show that the BP-BEC outperforms the no-BEC by about 60.1% and 73.6% in terms of positioning accuracy and robustness, respectively. Moreover, the execution time of the BP-BEC algorithm is also evaluated, and results show that the convergence speed of the proposed algorithm has an insignificant effect on real-time localization.

Improvement of vision measurement accuracy using Zernike moment based edge location error compensation model

International Nuclear Information System (INIS)

Cui, J W; Tan, J B; Zhou, Y; Zhang, H

2007-01-01

This paper presents the Zernike moment based model developed to compensate edge location errors for further improvement of the vision measurement accuracy by compensating the slight changes resulting from sampling and establishing mathematic expressions for subpixel location of theoretical and actual edges which are either vertical to or at an angle with X-axis. Experimental results show that the proposed model can be used to achieve a vision measurement accuracy of up to 0.08 pixel while the measurement uncertainty is less than 0.36μm. It is therefore concluded that as a model which can be used to achieve a significant improvement of vision measurement accuracy, the proposed model is especially suitable for edge location of images with low contrast

Low-frequency Periodic Error Identification and Compensation for Star Tracker Attitude Measurement

Institute of Scientific and Technical Information of China (English)

WANG Jiongqi; XIONG Kai; ZHOU Haiyin

2012-01-01

The low-frequency periodic error of star tracker is one of the most critical problems for high-accuracy satellite attitude determination.In this paper an approach is proposed to identify and compensate the low-frequency periodic error for star tracker in attitude measurement.The analytical expression between the estimated gyro drift and the low-frequency periodic error of star tracker is derived firstly.And then the low-frequency periodic error,which can be expressed by Fourier series,is identified by the frequency spectrum of the estimated gyro drift according to the solution of the first step.Furthermore,the compensated model of the low-frequency periodic error is established based on the identified parameters to improve the attitude determination accuracy.Finally,promising simulated experimental results demonstrate the validity and effectiveness of the proposed method.The periodic error for attitude determination is eliminated basically and the estimation precision is improved greatly.

Study of on-machine error identification and compensation methods for micro machine tools

International Nuclear Information System (INIS)

Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

2016-01-01

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

Compensation of position errors in passivity based teleoperation over packet switched communication networks

NARCIS (Netherlands)

Secchi, C; Stramigioli, Stefano; Fantuzzi, C.

Because of the use of scattering based communication channels, passivity based telemanipulation systems can be subject to a steady state position error between master and slave robots. In this paper, we consider the case in which the passive master and slave sides communicate through a packet

Neural networks based identification and compensation of rate-dependent hysteresis in piezoelectric actuators

International Nuclear Information System (INIS)

Zhang, Xinliang; Tan, Yonghong; Su, Miyong; Xie, Yangqiu

2010-01-01

This paper presents a method of the identification for the rate-dependent hysteresis in the piezoelectric actuator (PEA) by use of neural networks. In this method, a special hysteretic operator is constructed from the Prandtl-Ishlinskii (PI) model to extract the changing tendency of the static hysteresis. Then, an expanded input space is constructed by introducing the proposed hysteretic operator to transform the multi-valued mapping of the hysteresis into a one-to-one mapping. Thus, a feedforward neural network is applied to the approximation of the rate-independent hysteresis on the constructed expanded input space. Moreover, in order to describe the rate-dependent performance of the hysteresis, a special hybrid model, which is constructed by a linear auto-regressive exogenous input (ARX) sub-model preceded with the previously obtained neural network based rate-independent hysteresis sub-model, is proposed. For the compensation of the effect of the hysteresis in PEA, the PID feedback controller with a feedforward hysteresis compensator is developed for the tracking control of the PEA. Thus, a corresponding inverse model based on the proposed modeling method is developed for the feedforward hysteresis compensator. Finally, both simulations and experimental results on piezoelectric actuator are presented to verify the effectiveness of the proposed approach for the rate-dependent hysteresis.

An Experiment of GMPLS-Based Dispersion Compensation Control over In-Field Fibers

Science.gov (United States)

Seno, Shoichiro; Horiuchi, Eiichi; Yoshida, Sota; Sugihara, Takashi; Onohara, Kiyoshi; Kamei, Misato; Baba, Yoshimasa; Kubo, Kazuo; Mizuochi, Takashi

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24km and 360km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.

Error Concealment using Neural Networks for Block-Based Image Coding

Directory of Open Access Journals (Sweden)

M. Mokos

2006-06-01

Full Text Available In this paper, a novel adaptive error concealment (EC algorithm, which lowers the requirements for channel coding, is proposed. It conceals errors in block-based image coding systems by using neural network. In this proposed algorithm, only the intra-frame information is used for reconstruction of the image with separated damaged blocks. The information of pixels surrounding a damaged block is used to recover the errors using the neural network models. Computer simulation results show that the visual quality and the MSE evaluation of a reconstructed image are significantly improved using the proposed EC algorithm. We propose also a simple non-neural approach for comparison.

Effects of Target Positioning Error on Motion Compensation for Airborne Interferometric SAR

Directory of Open Access Journals (Sweden)

Li Yin-wei

2013-12-01

Full Text Available The measurement inaccuracies of Inertial Measurement Unit/Global Positioning System (IMU/GPS as well as the positioning error of the target may contribute to the residual uncompensated motion errors in the MOtion COmpensation (MOCO approach based on the measurement of IMU/GPS. Aiming at the effects of target positioning error on MOCO for airborne interferometric SAR, the paper firstly deduces a mathematical model of residual motion error bring out by target positioning error under the condition of squint. And the paper analyzes the effects on the residual motion error caused by system sampling delay error, the Doppler center frequency error and reference DEM error which result in target positioning error based on the model. Then, the paper discusses the effects of the reference DEM error on the interferometric SAR image quality, the interferometric phase and the coherent coefficient. The research provides theoretical bases for the MOCO precision in signal processing of airborne high precision SAR and airborne repeat-pass interferometric SAR.

Compensating for Type-I Errors in Video Quality Assessment

DEFF Research Database (Denmark)

Brunnström, Kjell; Tavakoli, Samira; Søgaard, Jacob

2015-01-01

This paper analyzes the impact on compensating for Type-I errors in video quality assessment. A Type-I error is to incorrectly conclude that there is an effect. The risk increases with the number of comparisons that are performed in statistical tests. Type-I errors are an issue often neglected...

Analysis and Compensation of Modulation Angular Rate Error Based on Missile-Borne Rotation Semi-Strapdown Inertial Navigation System

Directory of Open Access Journals (Sweden)

Jiayu Zhang

2018-05-01

Full Text Available The Semi-Strapdown Inertial Navigation System (SSINS provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS inertial measurement unit (MIMU outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions.

Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

Science.gov (United States)

Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

2016-01-01

The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052

Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

Directory of Open Access Journals (Sweden)

Roque Calvo

2016-09-01

Full Text Available The development of an error compensation model for coordinate measuring machines (CMMs and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included.

On the feedback error compensation for adaptive modulation and coding scheme

KAUST Repository

Choi, Seyeong

2011-11-25

In this paper, we consider the effect of feedback error on the performance of the joint adaptive modulation and diversity combining (AMDC) scheme which was previously studied with an assumption of perfect feedback channels. We quantify the performance of two joint AMDC schemes in the presence of feedback error, in terms of the average spectral efficiency, the average number of combined paths, and the average bit error rate. The benefit of feedback error compensation with adaptive combining is also quantified. Selected numerical examples are presented and discussed to illustrate the effectiveness of the proposed feedback error compensation strategy with adaptive combining. Copyright (c) 2011 John Wiley & Sons, Ltd.

Dependence of the compensation error on the error of a sensor and corrector in an adaptive optics phase-conjugating system

International Nuclear Information System (INIS)

Kiyko, V V; Kislov, V I; Ofitserov, E N

2015-01-01

In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)

Dependence of the compensation error on the error of a sensor and corrector in an adaptive optics phase-conjugating system

Energy Technology Data Exchange (ETDEWEB)

Kiyko, V V; Kislov, V I; Ofitserov, E N [A M Prokhorov General Physics Institute, Russian Academy of Sciences, Moscow (Russian Federation)

2015-08-31

In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)

Error compensation for hybrid-computer solution of linear differential equations

Science.gov (United States)

Kemp, N. H.

1970-01-01

Z-transform technique compensates for digital transport delay and digital-to-analog hold. Method determines best values for compensation constants in multi-step and Taylor series projections. Technique also provides hybrid-calculation error compared to continuous exact solution, plus system stability properties.

Analysis and Compensation for Gear Accuracy with Setting Error in Form Grinding

Directory of Open Access Journals (Sweden)

Chenggang Fang

2015-01-01

Full Text Available In the process of form grinding, gear setting error was the main factor that influenced the form grinding accuracy; we proposed an effective method to improve form grinding accuracy that corrected the error by controlling the machine operations. Based on establishing the geometry model of form grinding and representing the gear setting errors as homogeneous coordinate, tooth mathematic model was obtained and simplified under the gear setting error. Then, according to the gear standard of ISO1328-1: 1997 and the ANSI/AGMA 2015-1-A01: 2002, the relationship was investigated by changing the gear setting errors with respect to tooth profile deviation, helix deviation, and cumulative pitch deviation, respectively, under the condition of gear eccentricity error, gear inclination error, and gear resultant error. An error compensation method was proposed based on solving sensitivity coefficient matrix of setting error in a five-axis CNC form grinding machine; simulation and experimental results demonstrated that the method can effectively correct the gear setting error, as well as further improving the forming grinding accuracy.

Neural Network Based Real-time Correction of Transducer Dynamic Errors

Science.gov (United States)

Roj, J.

2013-12-01

In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.

Control of a hybrid compensator in a power network by an artificial neural network

Directory of Open Access Journals (Sweden)

I. S. Shaw

1998-07-01

Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

High-accuracy measurement and compensation of grating line-density error in a tiled-grating compressor

Science.gov (United States)

Zhao, Dan; Wang, Xiao; Mu, Jie; Li, Zhilin; Zuo, Yanlei; Zhou, Song; Zhou, Kainan; Zeng, Xiaoming; Su, Jingqin; Zhu, Qihua

2017-02-01

The grating tiling technology is one of the most effective means to increase the aperture of the gratings. The line-density error (LDE) between sub-gratings will degrade the performance of the tiling gratings, high accuracy measurement and compensation of the LDE are of significance to improve the output pulses characteristics of the tiled-grating compressor. In this paper, the influence of LDE on the output pulses of the tiled-grating compressor is quantitatively analyzed by means of numerical simulation, the output beams drift and output pulses broadening resulting from the LDE are presented. Based on the numerical results we propose a compensation method to reduce the degradations of the tiled grating compressor by applying angular tilt error and longitudinal piston error at the same time. Moreover, a monitoring system is setup to measure the LDE between sub-gratings accurately and the dispersion variation due to the LDE is also demonstrated based on spatial-spectral interference. In this way, we can realize high-accuracy measurement and compensation of the LDE, and this would provide an efficient way to guide the adjustment of the tiling gratings.

Error compensation of single-antenna attitude determination using GNSS for Low-dynamic applications

Science.gov (United States)

Chen, Wen; Yu, Chao; Cai, Miaomiao

2017-04-01

GNSS-based single-antenna pseudo-attitude determination method has attracted more and more attention from the field of high-dynamic navigation due to its low cost, low system complexity, and no temporal accumulated errors. Related researches indicate that this method can be an important complement or even an alternative to the traditional sensors for general accuracy requirement (such as small UAV navigation). The application of single-antenna attitude determining method to low-dynamic carrier has just started. Different from the traditional multi-antenna attitude measurement technique, the pseudo-attitude attitude determination method calculates the rotation angle of the carrier trajectory relative to the earth. Thus it inevitably contains some deviations comparing with the real attitude angle. In low-dynamic application, these deviations are particularly noticeable, which may not be ignored. The causes of the deviations can be roughly classified into three categories, including the measurement error, the offset error, and the lateral error. Empirical correction strategies for the formal two errors have been promoted in previous study, but lack of theoretical support. In this paper, we will provide quantitative description of the three type of errors and discuss the related error compensation methods. Vehicle and shipborne experiments were carried out to verify the feasibility of the proposed correction methods. Keywords: Error compensation; Single-antenna; GNSS; Attitude determination; Low-dynamic

Decomposition and correction overlapping peaks of LIBS using an error compensation method combined with curve fitting.

Science.gov (United States)

Tan, Bing; Huang, Min; Zhu, Qibing; Guo, Ya; Qin, Jianwei

2017-09-01

The laser induced breakdown spectroscopy (LIBS) technique is an effective method to detect material composition by obtaining the plasma emission spectrum. The overlapping peaks in the spectrum are a fundamental problem in the qualitative and quantitative analysis of LIBS. Based on a curve fitting method, this paper studies an error compensation method to achieve the decomposition and correction of overlapping peaks. The vital step is that the fitting residual is fed back to the overlapping peaks and performs multiple curve fitting processes to obtain a lower residual result. For the quantitative experiments of Cu, the Cu-Fe overlapping peaks in the range of 321-327 nm obtained from the LIBS spectrum of five different concentrations of CuSO 4 ·5H 2 O solution were decomposed and corrected using curve fitting and error compensation methods. Compared with the curve fitting method, the error compensation reduced the fitting residual about 18.12-32.64% and improved the correlation about 0.86-1.82%. Then, the calibration curve between the intensity and concentration of the Cu was established. It can be seen that the error compensation method exhibits a higher linear correlation between the intensity and concentration of Cu, which can be applied to the decomposition and correction of overlapping peaks in the LIBS spectrum.

Thermal error analysis and compensation for digital image/volume correlation

Science.gov (United States)

Pan, Bing

2018-02-01

Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

A Torque Error Compensation Algorithm for Surface Mounted Permanent Magnet Synchronous Machines with Respect to Magnet Temperature Variations

Directory of Open Access Journals (Sweden)

Chang-Seok Park

2017-09-01

Full Text Available This paper presents a torque error compensation algorithm for a surface mounted permanent magnet synchronous machine (SPMSM through real time permanent magnet (PM flux linkage estimation at various temperature conditions from medium to rated speed. As known, the PM flux linkage in SPMSMs varies with the thermal conditions. Since a maximum torque per ampere look up table, a control method used for copper loss minimization, is developed based on estimated PM flux linkage, variation of PM flux linkage results in undesired torque development of SPMSM drives. In this paper, PM flux linkage is estimated through a stator flux linkage observer and the torque error is compensated in real time using the estimated PM flux linkage. In this paper, the proposed torque error compensation algorithm is verified in simulation and experiment.

Analysis and compensation of synchronous measurement error for multi-channel laser interferometer

International Nuclear Information System (INIS)

Du, Shengwu; Hu, Jinchun; Zhu, Yu; Hu, Chuxiong

2017-01-01

Dual-frequency laser interferometer has been widely used in precision motion system as a displacement sensor, to achieve nanoscale positioning or synchronization accuracy. In a multi-channel laser interferometer synchronous measurement system, signal delays are different in the different channels, which will cause asynchronous measurement, and then lead to measurement error, synchronous measurement error (SME). Based on signal delay analysis of the measurement system, this paper presents a multi-channel SME framework for synchronous measurement, and establishes the model between SME and motion velocity. Further, a real-time compensation method for SME is proposed. This method has been verified in a self-developed laser interferometer signal processing board (SPB). The experiment result showed that, using this compensation method, at a motion velocity 0.89 m s −1 , the max SME between two measuring channels in the SPB is 1.1 nm. This method is more easily implemented and applied to engineering than the method of directly testing smaller signal delay. (paper)

Analysis and compensation of synchronous measurement error for multi-channel laser interferometer

Science.gov (United States)

Du, Shengwu; Hu, Jinchun; Zhu, Yu; Hu, Chuxiong

2017-05-01

Dual-frequency laser interferometer has been widely used in precision motion system as a displacement sensor, to achieve nanoscale positioning or synchronization accuracy. In a multi-channel laser interferometer synchronous measurement system, signal delays are different in the different channels, which will cause asynchronous measurement, and then lead to measurement error, synchronous measurement error (SME). Based on signal delay analysis of the measurement system, this paper presents a multi-channel SME framework for synchronous measurement, and establishes the model between SME and motion velocity. Further, a real-time compensation method for SME is proposed. This method has been verified in a self-developed laser interferometer signal processing board (SPB). The experiment result showed that, using this compensation method, at a motion velocity 0.89 m s-1, the max SME between two measuring channels in the SPB is 1.1 nm. This method is more easily implemented and applied to engineering than the method of directly testing smaller signal delay.

Study on Network Error Analysis and Locating based on Integrated Information Decision System

Science.gov (United States)

Yang, F.; Dong, Z. H.

2017-10-01

Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

Determination of optimal samples for robot calibration based on error similarity

Directory of Open Access Journals (Sweden)

Tian Wei

2015-06-01

Full Text Available Industrial robots are used for automatic drilling and riveting. The absolute position accuracy of an industrial robot is one of the key performance indexes in aircraft assembly, and can be improved through error compensation to meet aircraft assembly requirements. The achievable accuracy and the difficulty of accuracy compensation implementation are closely related to the choice of sampling points. Therefore, based on the error similarity error compensation method, a method for choosing sampling points on a uniform grid is proposed. A simulation is conducted to analyze the influence of the sample point locations on error compensation. In addition, the grid steps of the sampling points are optimized using a statistical analysis method. The method is used to generate grids and optimize the grid steps of a Kuka KR-210 robot. The experimental results show that the method for planning sampling data can be used to effectively optimize the sampling grid. After error compensation, the position accuracy of the robot meets the position accuracy requirements.

Identification-based chaos control via backstepping design using self-organizing fuzzy neural networks

International Nuclear Information System (INIS)

Peng Yafu; Hsu, C.-F.

2009-01-01

This paper proposes an identification-based adaptive backstepping control (IABC) for the chaotic systems. The IABC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SOFNN identifier. The SOFNN identifier is used to online estimate the chaotic dynamic function with structure and parameter learning phases of fuzzy neural network. The structure learning phase consists of the growing and pruning of fuzzy rules; thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the neural structure of fuzzy neural network. The parameter learning phase adjusts the interconnection weights of neural network to achieve favorable approximation performance. Finally, simulation results verify that the proposed IABC can achieve favorable tracking performance.

A measurement strategy and an error-compensation model for the on-machine laser measurement of large-scale free-form surfaces

International Nuclear Information System (INIS)

Li, Bin; Li, Feng; Liu, Hongqi; Cai, Hui; Mao, Xinyong; Peng, Fangyu

2014-01-01

This study presents a novel measurement strategy and an error-compensation model for the measurement of large-scale free-form surfaces in on-machine laser measurement systems. To improve the measurement accuracy, the effects of the scan depth, surface roughness, incident angle and azimuth angle on the measurement results were investigated experimentally, and a practical measurement strategy considering the position and orientation of the sensor is presented. Also, a semi-quantitative model based on geometrical optics is proposed to compensate for the measurement error associated with the incident angle. The normal vector of the measurement point is determined using a cross-curve method from the acquired surface data. Then, the azimuth angle and incident angle are calculated to inform the measurement strategy and error-compensation model, respectively. The measurement strategy and error-compensation model are verified through the measurement of a large propeller blade on a heavy machine tool in a factory environment. The results demonstrate that the strategy and the model are effective in increasing the measurement accuracy. (paper)

Compensation of kinematic geometric parameters error and comparative study of accuracy testing for robot

Science.gov (United States)

Du, Liang; Shi, Guangming; Guan, Weibin; Zhong, Yuansheng; Li, Jin

2014-12-01

Geometric error is the main error of the industrial robot, and it plays a more significantly important fact than other error facts for robot. The compensation model of kinematic error is proposed in this article. Many methods can be used to test the robot accuracy, therefore, how to compare which method is better one. In this article, a method is used to compare two methods for robot accuracy testing. It used Laser Tracker System (LTS) and Three Coordinate Measuring instrument (TCM) to test the robot accuracy according to standard. According to the compensation result, it gets the better method which can improve the robot accuracy apparently.

Design of a real-time spectroscopic rotating compensator ellipsometer without systematic errors

Energy Technology Data Exchange (ETDEWEB)

Broch, Laurent, E-mail: laurent.broch@univ-lorraine.fr [Laboratoire de Chimie Physique-Approche Multi-echelle des Milieux Complexes (LCP-A2MC, EA 4632), Universite de Lorraine, 1 boulevard Arago CP 87811, F-57078 Metz Cedex 3 (France); Stein, Nicolas [Institut Jean Lamour, Universite de Lorraine, UMR 7198 CNRS, 1 boulevard Arago CP 87811, F-57078 Metz Cedex 3 (France); Zimmer, Alexandre [Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS, Universite de Bourgogne, 9 avenue Alain Savary BP 47870, F-21078 Dijon Cedex (France); Battie, Yann; Naciri, Aotmane En [Laboratoire de Chimie Physique-Approche Multi-echelle des Milieux Complexes (LCP-A2MC, EA 4632), Universite de Lorraine, 1 boulevard Arago CP 87811, F-57078 Metz Cedex 3 (France)

2014-11-28

We describe a spectroscopic ellipsometer in the visible domain (400–800 nm) based on a rotating compensator technology using two detectors. The classical analyzer is replaced by a fixed Rochon birefringent beamsplitter which splits the incidence light wave into two perpendicularly polarized waves, one oriented at + 45° and the other one at − 45° according to the plane of incidence. Both emergent optical signals are analyzed by two identical CCD detectors which are synchronized by an optical encoder fixed on the shaft of the step-by-step motor of the compensator. The final spectrum is the result of the two averaged Ψ and Δ spectra acquired by both detectors. We show that Ψ and Δ spectra are acquired without systematic errors on a spectral range fixed from 400 to 800 nm. The acquisition time can be adjusted down to 25 ms. The setup was validated by monitoring the first steps of bismuth telluride film electrocrystallization. The results exhibit that induced experimental growth parameters, such as film thickness and volumic fraction of deposited material can be extracted with a better trueness. - Highlights: • High-speed rotating compensator ellipsometer equipped with 2 detectors. • Ellipsometric angles without systematic errors • In-situ monitoring of electrocrystallization of bismuth telluride thin layer • High-accuracy of fitted physical parameters.

NQAR: Network Quality Aware Routing in Error-Prone Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jaewon Choi

2010-01-01

Full Text Available We propose a network quality aware routing (NQAR mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR shows better performance than those routing methods in terms of jitter, reachability, and network lifetime.

Application of Joint Error Maximal Mutual Compensation to hexapod robots

DEFF Research Database (Denmark)

Veryha, Yauheni; Petersen, Henrik Gordon

2008-01-01

A good practice to ensure high-positioning accuracy in industrial robots is to use joint error maximum mutual compensation (JEMMC). This paper presents an application of JEMMC for positioning of hexapod robots to improve end-effector positioning accuracy. We developed an algorithm and simulation ...

Network compensation for missing sensors

Science.gov (United States)

Ahumada, Albert J., Jr.; Mulligan, Jeffrey B.

1991-01-01

A network learning translation invariance algorithm to compute interpolation functions is presented. This algorithm with one fixed receptive field can construct a linear transformation compensating for gain changes, sensor position jitter, and sensor loss when there are enough remaining sensors to adequately sample the input images. However, when the images are undersampled and complete compensation is not possible, the algorithm need to be modified. For moderate sensor losses, the algorithm works if the transformation weight adjustment is restricted to the weights to output units affected by the loss.

A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

Directory of Open Access Journals (Sweden)

Hu Ke-bin

2015-02-01

Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

Analysis of the Influence of Compensation Capacitance Errors of a Wireless Power Transfer System with SS Topology

Directory of Open Access Journals (Sweden)

Yi Wang

2017-12-01

Full Text Available In this study, in order to determine the reasonable accuracy of the compensation capacitances satisfying the requirements on the output characteristics for a wireless power transfer (WPT system, taking the series-series (SS compensation structure as an example, the calculation formulas of the output characteristics, such as the power factor, output power, coil transfer efficiency, and capacitors’ voltage stress, are given under the condition of incomplete compensation according to circuit theory. The influence of compensation capacitance errors on the output characteristics of the system is then analyzed. The Taylor expansions of the theoretical formulas are carried out to simplify the formulas. The influence degrees of compensation capacitance errors on the output characteristics are calculated according to the simplified formulas. The reasonable error ranges of the compensation capacitances are then determined according to the requirements of the output characteristics of the system in the system design. Finally, the validity of the theoretical analysis and the simplified processing is verified through experiments. The proposed method has a certain guiding role for practical engineering design, especially in mass production.

A Novel Time-Varying Friction Compensation Method for Servomechanism

Directory of Open Access Journals (Sweden)

Bin Feng

2015-01-01

Full Text Available Friction is an inevitable nonlinear phenomenon existing in servomechanisms. Friction errors often affect their motion and contour accuracies during the reverse motion. To reduce friction errors, a novel time-varying friction compensation method is proposed to solve the problem that the traditional friction compensation methods hardly deal with. This problem leads to an unsatisfactory friction compensation performance and the motion and contour accuracies cannot be maintained effectively. In this method, a trapezoidal compensation pulse is adopted to compensate for the friction errors. A generalized regression neural network algorithm is used to generate the optimal pulse amplitude function. The optimal pulse duration function and the pulse amplitude function can be established by the pulse characteristic parameter learning and then the optimal friction compensation pulse can be generated. The feasibility of friction compensation method was verified on a high-precision X-Y worktable. The experimental results indicated that the motion and contour accuracies were improved greatly with reduction of the friction errors, in different working conditions. Moreover, the overall friction compensation performance indicators were decreased by more than 54% and this friction compensation method can be implemented easily on most of servomechanisms in industry.

Linear network error correction coding

CERN Document Server

Guang, Xuan

2014-01-01

There are two main approaches in the theory of network error correction coding. In this SpringerBrief, the authors summarize some of the most important contributions following the classic approach, which represents messages by sequences?similar to algebraic coding,?and also briefly discuss the main results following the?other approach,?that uses the theory of rank metric codes for network error correction of representing messages by subspaces. This book starts by establishing the basic linear network error correction (LNEC) model and then characterizes two equivalent descriptions. Distances an

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation

Directory of Open Access Journals (Sweden)

Jianzhong Zhou

2017-12-01

Full Text Available Model simulation and control of pumped storage unit (PSU are essential to improve the dynamic quality of power station. Only under the premise of the PSU models reflecting the actual transient process, the novel control method can be properly applied in the engineering. The contributions of this paper are that (1 a real-time accurate equivalent circuit model (RAECM of PSU via error compensation is proposed to reconcile the conflict between real-time online simulation and accuracy under various operating conditions, and (2 an adaptive predicted fuzzy PID controller (APFPID based on RAECM is put forward to overcome the instability of conventional control under no-load conditions with low water head. Respectively, all hydraulic factors in pipeline system are fully considered based on equivalent lumped-circuits theorem. The pretreatment, which consists of improved Suter-transformation and BP neural network, and online simulation method featured by two iterative loops are synthetically proposed to improve the solving accuracy of the pump-turbine. Moreover, the modified formulas for compensating error are derived with variable-spatial discretization to improve the accuracy of the real-time simulation further. The implicit RadauIIA method is verified to be more suitable for PSUGS owing to wider stable domain. Then, APFPID controller is constructed based on the integration of fuzzy PID and the model predictive control. Rolling prediction by RAECM is proposed to replace rolling optimization with its computational speed guaranteed. Finally, the simulation and on-site measurements are compared to prove trustworthy of RAECM under various running conditions. Comparative experiments also indicate that APFPID controller outperforms other controllers in most cases, especially low water head conditions. Satisfying results of RAECM have been achieved in engineering and it provides a novel model reference for PSUGS.

Springback Compensation Based on FDM-DTF Method

International Nuclear Information System (INIS)

Liu Qiang; Kang Lan

2010-01-01

Stamping part error caused by springback is usually considered to be a tooling defect in sheet metal forming process. This problem can be corrected by adjusting the tooling shape to appropriate shape. In this paper, springback compensation based on FDM-DTF method is proposed to be used for design and modification of the tooling shape. Firstly, based on FDM method, the tooling shape is designed by reversing inner force's direction at the end of forming simulation, the required tooling shape can be got through some iterations. Secondly actual tooling is produced based on results got in the first step. When the tooling and part surface discrete data are investigated, the transfer function between numerical springback error and real springback error can be calculated based on wavelet transform results, which can be used in predicting the tooling shape for the desired product. Finally the FDM-DTF method is proved to control springback effectively after it has been applied in the 2D irregular product springback control.

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah

2015-01-01

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485

The analysis and compensation of errors of precise simple harmonic motion control under high speed and large load conditions based on servo electric cylinder

Science.gov (United States)

Ma, Chen-xi; Ding, Guo-qing

2017-10-01

Simple harmonic waves and synthesized simple harmonic waves are widely used in the test of instruments. However, because of the errors caused by clearance of gear and time-delay error of FPGA, it is difficult to control servo electric cylinder in precise simple harmonic motion under high speed, high frequency and large load conditions. To solve the problem, a method of error compensation is proposed in this paper. In the method, a displacement sensor is fitted on the piston rod of the electric cylinder. By using the displacement sensor, the real-time displacement of the piston rod is obtained and fed back to the input of servo motor, then a closed loop control is realized. There is compensation of pulses in the next period of the synthetic waves. This paper uses FPGA as the processing core. The software mainly comprises a waveform generator, an Ethernet module, a memory module, a pulse generator, a pulse selector, a protection module, an error compensation module. A durability of shock absorbers is used as the testing platform. The durability mainly comprises a single electric cylinder, a servo motor for driving the electric cylinder, and the servo motor driver.

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Directory of Open Access Journals (Sweden)

Mohammad Abdur Razzaque

2014-12-01

Full Text Available Wireless body sensor networks (WBSNs for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS, in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network’s QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

Dynamic Compensation for Two-Axis Robot Wrist Force Sensors

Directory of Open Access Journals (Sweden)

Junqing Ma

2013-01-01

Full Text Available To improve the dynamic characteristic of two-axis force sensors, a dynamic compensation method is proposed. The two-axis force sensor system is assumed to be a first-order system. The operation frequency of the system is expanded by a digital filter with backward difference network. To filter high-frequency noises, a low-pass filter is added after the dynamic compensation network. To avoid overcompensation, parameters of the proposed dynamic compensation method are defined by trial and error. Step response methods are utilized in dynamic calibration experiments. Compared to experiment data without compensation, the response time of the dynamic compensated data is reduced by 30%~40%. Experiments results demonstrate the effectiveness of our method.

A novel PON based UMTS broadband wireless access network architecture with an algorithm to guarantee end to end QoS

Science.gov (United States)

Sana, Ajaz; Hussain, Shahab; Ali, Mohammed A.; Ahmed, Samir

2007-09-01

In this paper we proposes a novel Passive Optical Network (PON) based broadband wireless access network architecture to provide multimedia services (video telephony, video streaming, mobile TV, mobile emails etc) to mobile users. In the conventional wireless access networks, the base stations (Node B) and Radio Network Controllers (RNC) are connected by point to point T1/E1 lines (Iub interface). The T1/E1 lines are expensive and add up to operating costs. Also the resources (transceivers and T1/E1) are designed for peak hours traffic, so most of the time the dedicated resources are idle and wasted. Further more the T1/E1 lines are not capable of supporting bandwidth (BW) required by next generation wireless multimedia services proposed by High Speed Packet Access (HSPA, Rel.5) for Universal Mobile Telecommunications System (UMTS) and Evolution Data only (EV-DO) for Code Division Multiple Access 2000 (CDMA2000). The proposed PON based back haul can provide Giga bit data rates and Iub interface can be dynamically shared by Node Bs. The BW is dynamically allocated and the unused BW from lightly loaded Node Bs is assigned to heavily loaded Node Bs. We also propose a novel algorithm to provide end to end Quality of Service (QoS) (between RNC and user equipment).The algorithm provides QoS bounds in the wired domain as well as in wireless domain with compensation for wireless link errors. Because of the air interface there can be certain times when the user equipment (UE) is unable to communicate with Node B (usually referred to as link error). Since the link errors are bursty and location dependent. For a proposed approach, the scheduler at the Node B maps priorities and weights for QoS into wireless MAC. The compensations for errored links is provided by the swapping of services between the active users and the user data is divided into flows, with flows allowed to lag or lead. The algorithm guarantees (1)delay and throughput for error-free flows,(2)short term fairness

Bayesian network models for error detection in radiotherapy plans

International Nuclear Information System (INIS)

Kalet, Alan M; Ford, Eric C; Phillips, Mark H; Gennari, John H

2015-01-01

The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures. (paper)

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks.

Science.gov (United States)

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.

[Study on the Effects and Compensation Effect of Recording Parameters Error on Imaging Performance of Holographic Grating in On-Line Spectral Diagnose].

Science.gov (United States)

Jiang, Yan-xiu; Bayanheshig; Yang, Shuo; Zhao, Xu-long; Wu, Na; Li, Wen-hao

2016-03-01

To making the high resolution grating, a numerical calculation was used to analyze the effect of recording parameters on groove density, focal curve and imaging performance of the grating and their compensation. Based on Fermat' s principle, light path function and aberration, the effect on imaging performance of the grating was analyzed. In the case of fixed using parameters, the error of the recording angle has a greater influence on imaging performance, therefore the gain of the weight of recording angle can improve the accuracy of the recording angle values in the optimization; recording distance has little influence on imaging performance; the relative errors of recording parameters cause the change of imaging performance of the grating; the results indicate that recording parameter errors can be compensated by adjusting its corresponding parameter. The study can give theoretical guidance to the fabrication for high resolution varied-line-space plane holographic grating in on-line spectral diagnostic and reduce the alignment difficulty by analyze the main error effect the imaging performance and propose the compensation method.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN.

Science.gov (United States)

Marques, Luis; Vasconcelos, Verónica; Pedreiras, Paulo; Almeida, Luís

2018-01-11

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

Compensating additional optical power in the central zone of a multifocal contact lens forminimization of the shrinkage error of the shell mold in the injection molding process.

Science.gov (United States)

Vu, Lien T; Chen, Chao-Chang A; Lee, Chia-Cheng; Yu, Chia-Wei

2018-04-20

This study aims to develop a compensating method to minimize the shrinkage error of the shell mold (SM) in the injection molding (IM) process to obtain uniform optical power in the central optical zone of soft axial symmetric multifocal contact lenses (CL). The Z-shrinkage error along the Z axis or axial axis of the anterior SM corresponding to the anterior surface of a dry contact lens in the IM process can be minimized by optimizing IM process parameters and then by compensating for additional (Add) powers in the central zone of the original lens design. First, the shrinkage error is minimized by optimizing three levels of four IM parameters, including mold temperature, injection velocity, packing pressure, and cooling time in 18 IM simulations based on an orthogonal array L 18 (2 1 ×3 4 ). Then, based on the Z-shrinkage error from IM simulation, three new contact lens designs are obtained by increasing the Add power in the central zone of the original multifocal CL design to compensate for the optical power errors. Results obtained from IM process simulations and the optical simulations show that the new CL design with 0.1 D increasing in Add power has the closest shrinkage profile to the original anterior SM profile with percentage of reduction in absolute Z-shrinkage error of 55% and more uniform power in the central zone than in the other two cases. Moreover, actual experiments of IM of SM for casting soft multifocal CLs have been performed. The final product of wet CLs has been completed for the original design and the new design. Results of the optical performance have verified the improvement of the compensated design of CLs. The feasibility of this compensating method has been proven based on the measurement results of the produced soft multifocal CLs of the new design. Results of this study can be further applied to predict or compensate for the total optical power errors of the soft multifocal CLs.

Beam-pointing error compensation method of phased array radar seeker with phantom-bit technology

Directory of Open Access Journals (Sweden)

Qiuqiu WEN

2017-06-01

Full Text Available A phased array radar seeker (PARS must be able to effectively decouple body motion and accurately extract the line-of-sight (LOS rate for target missile tracking. In this study, the real-time two-channel beam pointing error (BPE compensation method of PARS for LOS rate extraction is designed. The PARS discrete beam motion principium is analyzed, and the mathematical model of beam scanning control is finished. According to the principle of the antenna element shift phase, both the antenna element shift phase law and the causes of beam-pointing error under phantom-bit conditions are analyzed, and the effect of BPE caused by phantom-bit technology (PBT on the extraction accuracy of the LOS rate is examined. A compensation method is given, which includes coordinate transforms, beam angle margin compensation, and detector dislocation angle calculation. When the method is used, the beam angle margin in the pitch and yaw directions is calculated to reduce the effect of the missile body disturbance and to improve LOS rate extraction precision by compensating for the detector dislocation angle. The simulation results validate the proposed method.

Neural network error correction for solving coupled ordinary differential equations

Science.gov (United States)

Shelton, R. O.; Darsey, J. A.; Sumpter, B. G.; Noid, D. W.

1992-01-01

A neural network is presented to learn errors generated by a numerical algorithm for solving coupled nonlinear differential equations. The method is based on using a neural network to correctly learn the error generated by, for example, Runge-Kutta on a model molecular dynamics (MD) problem. The neural network programs used in this study were developed by NASA. Comparisons are made for training the neural network using backpropagation and a new method which was found to converge with fewer iterations. The neural net programs, the MD model and the calculations are discussed.

Mixed error compensation in a heterodyne interferometer using the iterated dual-EKF algorithm

International Nuclear Information System (INIS)

Lee, Woo Ram; Kim, Chang Rai; You, Kwan Ho

2010-01-01

The heterodyne laser interferometer has been widely used in the field of precise measurements. The limited measurement accuracy of a heterodyne laser interferometer arises from the periodic nonlinearity caused by non-ideal laser sources and imperfect optical components. In this paper, the iterated dual-EKF algorithm is used to compensate for the error caused by nonlinearity and external noise. With the iterated dual-EKF algorithm, the weight filter estimates the parameter uncertainties in the state equation caused by nonlinearity errors and has a high convergence rate of weight values due to the iteration process. To verify the performance of the proposed compensation algorithm, we present experimental results obtained by using the iterated dual-EKF algorithm and compare them with the results obtained by using a capacitance displacement sensor.

Mixed error compensation in a heterodyne interferometer using the iterated dual-EKF algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Woo Ram; Kim, Chang Rai; You, Kwan Ho [Sungkyunkwan University, Suwon (Korea, Republic of)

2010-10-15

The heterodyne laser interferometer has been widely used in the field of precise measurements. The limited measurement accuracy of a heterodyne laser interferometer arises from the periodic nonlinearity caused by non-ideal laser sources and imperfect optical components. In this paper, the iterated dual-EKF algorithm is used to compensate for the error caused by nonlinearity and external noise. With the iterated dual-EKF algorithm, the weight filter estimates the parameter uncertainties in the state equation caused by nonlinearity errors and has a high convergence rate of weight values due to the iteration process. To verify the performance of the proposed compensation algorithm, we present experimental results obtained by using the iterated dual-EKF algorithm and compare them with the results obtained by using a capacitance displacement sensor.

Knowledge-Based Trajectory Error Pattern Method Applied to an Active Force Control Scheme

Directory of Open Access Journals (Sweden)

Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin

2012-08-01

Full Text Available The active force control (AFC method is known as a robust control scheme that dramatically enhances the performance of a robot arm particularly in compensating the disturbance effects. The main task of the AFC method is to estimate the inertia matrix in the feedback loop to provide the correct (motor torque required to cancel out these disturbances. Several intelligent control schemes have already been introduced to enhance the estimation methods of acquiring the inertia matrix such as those using neural network, iterative learning and fuzzy logic. In this paper, we propose an alternative scheme called Knowledge-Based Trajectory Error Pattern Method (KBTEPM to suppress the trajectory track error of the AFC scheme. The knowledge is developed from the trajectory track error characteristic based on the previous experimental results of the crude approximation method. It produces a unique, new and desirable error pattern when a trajectory command is forced. An experimental study was performed using simulation work on the AFC scheme with KBTEPM applied to a two-planar manipulator in which a set of rule-based algorithm is derived. A number of previous AFC schemes are also reviewed as benchmark. The simulation results show that the AFC-KBTEPM scheme successfully reduces the trajectory track error significantly even in the presence of the introduced disturbances.Key Words:  Active force control, estimated inertia matrix, robot arm, trajectory error pattern, knowledge-based.

An error compensation method for a linear array sun sensor with a V-shaped slit

International Nuclear Information System (INIS)

Fan, Qiao-yun; Tan, Xiao-feng

2015-01-01

Existing methods of improving measurement accuracy, such as polynomial fitting and increasing pixel numbers, cannot guarantee high precision and good miniaturization specifications of a microsun sensor at the same time. Therefore, a novel integrated and accurate error compensation method is proposed. A mathematical error model is established according to the analysis results of all the contributing factors, and the model parameters are calculated through multi-sets simultaneous calibration. The numerical simulation results prove that the calibration method is unaffected by installation errors introduced by the calibration process, and is capable of separating the sensor’s intrinsic and extrinsic parameters precisely, and obtaining accurate and robust intrinsic parameters. In laboratorial calibration, the calibration data are generated by using a two-axis rotation table and a sun simulator. The experimental results show that owing to the proposed error compensation method, the sun sensor’s measurement accuracy is improved by 30 times throughout its field of view (±60°  ×  ±60°), with a RMS error of 0.1°. (paper)

Quantitative analysis of scaling error compensation methods in dimensional X-ray computed tomography

DEFF Research Database (Denmark)

Müller, P.; Hiller, Jochen; Dai, Y.

2015-01-01

X-ray Computed Tomography (CT) has become an important technology for quality control of industrial components. As with other technologies, e.g., tactile coordinate measurements or optical measurements, CT is influenced by numerous quantities which may have negative impact on the accuracy...... errors of the manipulator system (magnification axis). This article also introduces a new compensation method for scaling errors using a database of reference scaling factors and discusses its advantages and disadvantages. In total, three methods for the correction of scaling errors – using the CT ball...

Artificial neural network implementation of a near-ideal error prediction controller

Science.gov (United States)

Mcvey, Eugene S.; Taylor, Lynore Denise

1992-01-01

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error

Accuracy Enhancement with Processing Error Prediction and Compensation of a CNC Flame Cutting Machine Used in Spatial Surface Operating Conditions

Directory of Open Access Journals (Sweden)

Shenghai Hu

2017-04-01

Full Text Available This study deals with the precision performance of the CNC flame-cutting machine used in spatial surface operating conditions and presents an accuracy enhancement method based on processing error modeling prediction and real-time compensation. Machining coordinate systems and transformation matrix models were established for the CNC flame processing system considering both geometric errors and thermal deformation effects. Meanwhile, prediction and compensation models were constructed related to the actual cutting situation. Focusing on the thermal deformation elements, finite element analysis was used to measure the testing data of thermal errors, the grey system theory was applied to optimize the key thermal points, and related thermal dynamics models were carried out to achieve high-precision prediction values. Comparison experiments between the proposed method and the teaching method were conducted on the processing system after performing calibration. The results showed that the proposed method is valid and the cutting quality could be improved by more than 30% relative to the teaching method. Furthermore, the proposed method can be used under any working condition by making a few adjustments to the prediction and compensation models.

Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays

Directory of Open Access Journals (Sweden)

Yeun-Sub Byun

2015-11-01

Full Text Available The real-time recognition of absolute (or relative position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test.

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Directory of Open Access Journals (Sweden)

Yunhan Lin

2016-01-01

Full Text Available It is a necessary mean to realize the accurate motion control of the manipulator which uses end-effector pose correction method and compensation method. In this article, first, we established the kinematic model and error model of the modular manipulator (WUST-ARM, and then we discussed the measurement methods and precision of the inertial measurement unit sensor. The inertial measurement unit sensor is mounted on the end-effector of modular manipulator, to get the real-time pose of the end-effector. At last, a new inertial measurement unit–based iterative pose compensation algorithm is proposed. By applying this algorithm in the pose compensation experiment of modular manipulator which is composed of low-cost rotation joints, the results show that the inertial measurement unit can obtain a higher precision when in static state; it will accurately feedback to the control system with an accurate error compensation angle after a brief delay when the end-effector moves to the target point, and after compensation, the precision errors of roll angle, pitch angle, and yaw angle are reached at 0.05°, 0.01°, and 0.27° respectively. It proves that this low-cost method provides a new solution to improve the end-effector pose of low-cost modular manipulator.

A Survey of Wireless Fair Queuing Algorithms with Location-Dependent Channel Errors

Directory of Open Access Journals (Sweden)

Anca VARGATU

2011-01-01

Full Text Available The rapid development of wireless networks has brought more and more attention to topics related to fair allocation of resources, creation of suitable algorithms, taking into account the special characteristics of wireless environment and insurance fair access to the transmission channel, with delay bound and throughput guaranteed. Fair allocation of resources in wireless networks requires significant challenges, because of errors that occur only in these networks, such as location-dependent and bursty channel errors. In wireless networks, frequently happens, because interference of radio waves, that a user experiencing bad radio conditions during a period of time, not to receive resources in that period. This paper analyzes some resource allocation algorithms for wireless networks with location dependent errors, specifying the base idea for each algorithm and the way how it works. The analyzed fair queuing algorithms differ by the way they treat the following aspects: how to select the flows which should receive additional services, how to allocate these resources, which is the proportion received by error free flows and how the flows affected by errors are compensated.

A New Control Structure for Grid-Connected LCL PV Inverters with Zero Steady-State Error and Selective Harmonic Compensation

DEFF Research Database (Denmark)

Teodorescu, Remus; Blaabjerg, Frede; Borup, Uffe

2004-01-01

disturbance rejection capability leads to the need of grid feed-forward compensation. However the imperfect compensation action of the feed-forward control results in high harmonic distortion of the current and consequently non-compliance with international standards. In this paper a new control strategy...... aimed to mitigate these problems is proposed. Stationary-frame generalized integrators are used to control the fundamental current and to compensate the grid harmonics providing disturbance rejection capability without the need of feed-forward grid compensation. Moreover the use of a grid LCL......The PI current control of a single-phase inverter has well known drawbacks: steady-state magnitude and phase-error and limited disturbance rejection capability. When the current controlled inverter is connected to the grid, the phase error results in a power factor decrement and the limited...

Application of static var compensator on large synchronous motors based on linear optimization control design

International Nuclear Information System (INIS)

Soltani, J.; Fath Abadi, A.M.

2003-01-01

This paper describes the application of static var compensators, on an electrical distribution network containing two large synchronous motors, one of which is excited via a three-phase thyristor bridge rectifier. The second machine is excited via a diode bridge rectifier. Based on linear optimization control, the measurable feedback signals are applied to the control system loops of static var compensators and the excitation control loop of the first synchronous motor. The phase equations method was used to develop a computer program to model the distribution network. Computer results were obtained to demonstrate the system performance for some abnormal modes of operation. These results show that employing static var compensators based on the linear optimization control design for electrical distribution networks containing large synchronous motors is beneficial and may be considered a first stage of the system design

Evaluation of slow shutdown system flux detectors in Point Lepreau Generating Station - II: dynamic compensation error analysis

Energy Technology Data Exchange (ETDEWEB)

Anghel, V.N.P.; Sur, B. [Atomic Energy of Canada Limited, Chalk River, Ontario (Canada); Taylor, D. [New Brunswick Power Nuclear, Point Lepreau, New Brunswick (Canada)

2009-07-01

CANDU reactors are protected against reactor overpower by two independent shutdown systems: Shut Down System 1 and 2 (SDS1 and SDS2). At the Point Lepreau Generating Station (PLGS), the shutdown systems can be actuated by measurements of the neutron flux from Platinum-clad Inconel In-Core Flux Detectors. These detectors have a complex dynamic behaviour, characterized by 'prompt' and 'delayed' components with respect to immediate changes in the in-core neutron flux. It was shown previously (I: Dynamic Response Characterization by Anghel et al., this conference) that the dynamic responses of the detectors changed with irradiation, with the SDS2 detectors having 'prompt' signal components that decreased significantly. In this paper we assess the implication of these changes for detector dynamic compensation errors by comparing the compensated detector response with the power-to-fuel and the power-to-coolant responses to neutron flux ramps as assumed by previous error analyses. The dynamic compensation error is estimated at any given trip time for all possible accident flux ramps. Some implications for the shutdown system trip set points, obtained from preliminary results, are discussed. (author)

Defaunation leads to interaction deficits, not interaction compensation, in an island seed dispersal network.

Science.gov (United States)

Fricke, Evan C; Tewksbury, Joshua J; Rogers, Haldre S

2018-01-01

Following defaunation, the loss of interactions with mutualists such as pollinators or seed dispersers may be compensated through increased interactions with remaining mutualists, ameliorating the negative cascading impacts on biodiversity. Alternatively, remaining mutualists may respond to altered competition by reducing the breadth or intensity of their interactions, exacerbating negative impacts on biodiversity. Despite the importance of these responses for our understanding of the dynamics of mutualistic networks and their response to global change, the mechanism and magnitude of interaction compensation within real mutualistic networks remains largely unknown. We examined differences in mutualistic interactions between frugivores and fruiting plants in two island ecosystems possessing an intact or disrupted seed dispersal network. We determined how changes in the abundance and behavior of remaining seed dispersers either increased mutualistic interactions (contributing to "interaction compensation") or decreased interactions (causing an "interaction deficit") in the disrupted network. We found a "rich-get-richer" response in the disrupted network, where remaining frugivores favored the plant species with highest interaction frequency, a dynamic that worsened the interaction deficit among plant species with low interaction frequency. Only one of five plant species experienced compensation and the other four had significant interaction deficits, with interaction frequencies 56-95% lower in the disrupted network. These results do not provide support for the strong compensating mechanisms assumed in theoretical network models, suggesting that existing network models underestimate the prevalence of cascading mutualism disruption after defaunation. This work supports a mutualist biodiversity-ecosystem functioning relationship, highlighting the importance of mutualist diversity for sustaining diverse and resilient ecosystems. © 2017 John Wiley & Sons Ltd.

Analysis on the dynamic error for optoelectronic scanning coordinate measurement network

Science.gov (United States)

Shi, Shendong; Yang, Linghui; Lin, Jiarui; Guo, Siyang; Ren, Yongjie

2018-01-01

Large-scale dynamic three-dimension coordinate measurement technique is eagerly demanded in equipment manufacturing. Noted for advantages of high accuracy, scale expandability and multitask parallel measurement, optoelectronic scanning measurement network has got close attention. It is widely used in large components jointing, spacecraft rendezvous and docking simulation, digital shipbuilding and automated guided vehicle navigation. At present, most research about optoelectronic scanning measurement network is focused on static measurement capacity and research about dynamic accuracy is insufficient. Limited by the measurement principle, the dynamic error is non-negligible and restricts the application. The workshop measurement and positioning system is a representative which can realize dynamic measurement function in theory. In this paper we conduct deep research on dynamic error resources and divide them two parts: phase error and synchronization error. Dynamic error model is constructed. Based on the theory above, simulation about dynamic error is carried out. Dynamic error is quantized and the rule of volatility and periodicity has been found. Dynamic error characteristics are shown in detail. The research result lays foundation for further accuracy improvement.

Research on State-of-Charge (SOC) estimation using current integration based on temperature compensation

Science.gov (United States)

Yin, J.; Shen, Y.; Liu, X. T.; Zeng, G. J.; Liu, D. C.

2017-11-01

The traditional current integral method for the state-of-charge (SOC) estimation has an unusable estimation accuracy because of the current measuring error. This paper proposed a closed-loop temperature compensation method to improve the SOC estimation accuracy of current integral method by eliminating temperature drift. Through circuit simulation result in Multisim, the stability of current measuring accuracy is improved by more than 10 times. In a designed 70 charge-discharge experimental circle, the SOC estimation error with temperature compensation had 30 times less than error in normal situation without compensation.

Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control

Directory of Open Access Journals (Sweden)

YanBin Liu

2017-01-01

Full Text Available The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller.

Cell outage compensation in LTE networks: Algorithms and performance assessment

NARCIS (Netherlands)

Amirijoo, M.; Jorguseski, L.; Litjens, R.; Schmelz, L.C.

2011-01-01

Cell outage compensation is a self-healing function and as such part of the Self-Organising Networks concept for mobile wireless networks. It aims at mitigating the degradation of coverage, capacity and service quality caused by a cell or site level outage. Upon detection of such an outage, cell

Numerical tilting compensation in microscopy based on wavefront sensing using transport of intensity equation method

Science.gov (United States)

Hu, Junbao; Meng, Xin; Wei, Qi; Kong, Yan; Jiang, Zhilong; Xue, Liang; Liu, Fei; Liu, Cheng; Wang, Shouyu

2018-03-01

Wide-field microscopy is commonly used for sample observations in biological research and medical diagnosis. However, the tilting error induced by the oblique location of the image recorder or the sample, as well as the inclination of the optical path often deteriorates the imaging quality. In order to eliminate the tilting in microscopy, a numerical tilting compensation technique based on wavefront sensing using transport of intensity equation method is proposed in this paper. Both the provided numerical simulations and practical experiments prove that the proposed technique not only accurately determines the tilting angle with simple setup and procedures, but also compensates the tilting error for imaging quality improvement even in the large tilting cases. Considering its simple systems and operations, as well as image quality improvement capability, it is believed the proposed method can be applied for tilting compensation in the optical microscopy.

Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

Directory of Open Access Journals (Sweden)

Chih-Hong Kao

2011-01-01

Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

Error estimation of deformable image registration of pulmonary CT scans using convolutional neural networks.

Science.gov (United States)

Eppenhof, Koen A J; Pluim, Josien P W

2018-04-01

Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D convolutional neural network that learns to estimate registration errors from a pair of image patches. By applying the network to patches centered around every voxel, we construct registration error maps. The network is trained using a set of representative images that have been synthetically transformed to construct a set of image pairs with known deformations. The method is evaluated on deformable registrations of inhale-exhale pairs of thoracic CT scans. Using ground truth target registration errors on manually annotated landmarks, we evaluate the method's ability to estimate local registration errors. Estimation of full domain error maps is evaluated using a gold standard approach. The two evaluation approaches show that we can train the network to robustly estimate registration errors in a predetermined range, with subvoxel accuracy. We achieved a root-mean-square deviation of 0.51 mm from gold standard registration errors and of 0.66 mm from ground truth landmark registration errors.

Conjugate descent formulation of backpropagation error in feedforward neural networks

Directory of Open Access Journals (Sweden)

NK Sharma

2009-06-01

Full Text Available The feedforward neural network architecture uses backpropagation learning to determine optimal weights between different interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to minimise the error function for a given set of patterns, by adjusting the weights of the network. The first derivates of the error with respect to the weights identify the local error surface in the descent direction. Hence the network exhibits a different local error surface for every different pattern presented to it, and weights are iteratively modified in order to minimise the current local error. The determination of an optimal weight vector is possible only when the total minimum error (mean of the minimum local errors for all patterns from the training set may be minimised. In this paper, we present a general mathematical formulation for the second derivative of the error function with respect to the weights (which represents a conjugate descent for arbitrary feedforward neural network topologies, and we use this derivative information to obtain the optimal weight vector. The local error is backpropagated among the units of hidden layers via the second order derivative of the error with respect to the weights of the hidden and output layers independently and also in combination. The new total minimum error point may be evaluated with the help of the current total minimum error and the current minimised local error. The weight modification processes is performed twice: once with respect to the present local error and once more with respect to the current total or mean error. We present some numerical evidence that our proposed method yields better network weights than those determined via a conventional gradient descent approach.

Compensation for unmatched uncertainty with adaptive RBF network

African Journals Online (AJOL)

Robust control for nonlinear uncertain systems has been solved for matched uncertainty but has not been completely solved yet for unmatched uncertainty. This paper developed a new method in which an adaptive radial basis function neural network is used to compensate for the effects of unmatched uncertainty in the ...

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Science.gov (United States)

Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

2014-07-01

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This

Low-Cost Ultrasonic Distance Sensor Arrays with Networked Error Correction

Directory of Open Access Journals (Sweden)

Tianzhou Chen

2013-09-01

Full Text Available Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation.

Differential Laser Doppler based Non-Contact Sensor for Dimensional Inspection with Error Propagation Evaluation

Directory of Open Access Journals (Sweden)

Ketsaya Vacharanukul

2006-06-01

Full Text Available To achieve dynamic error compensation in CNC machine tools, a non-contactlaser probe capable of dimensional measurement of a workpiece while it is being machinedhas been developed and presented in this paper. The measurements are automatically fedback to the machine controller for intelligent error compensations. Based on a well resolvedlaser Doppler technique and real time data acquisition, the probe delivers a very promisingdimensional accuracy at few microns over a range of 100 mm. The developed opticalmeasuring apparatus employs a differential laser Doppler arrangement allowing acquisitionof information from the workpiece surface. In addition, the measurements are traceable tostandards of frequency allowing higher precision.

Ionospheric errors compensation for ground deformation estimation with new generation SAR

Science.gov (United States)

Gomba, Giorgio; De Zan, Francesco; Rodriguez Gonzalez, Fernando

2017-04-01

Synthetic aperture radar (SAR) and interferometric SAR (InSAR) measurements are disturbed by the propagation velocity changes of microwaves that are caused by the high density of free electrons in the ionosphere. Most affected are low-frequency (L- or P-band) radars, as the recently launched ALOS-2 and the future Tandem-L and NISAR, although higher frequency (C- or X-band) systems, as the recently launched Sentinel-1, are not immune. Since the ionosphere is an obstacle to increasing the precision of new generation SAR systems needed to remotely measure the Earth's dynamic processes as for example ground deformation, it is necessary to estimate and compensate ionospheric propagation delays in SAR signals. In this work we discuss about the influence of the ionosphere on interferograms and the possible correction methods with relative accuracies. Consequently, the effect of ionospheric induced errors on ground deformation measurements prior and after ionosphere compensation will be analyzed. Examples will be presented of corrupted measurements of earthquakes and fault motion along with the corrected results using different methods.

Multi-qubit compensation sequences

International Nuclear Information System (INIS)

Tomita, Y; Merrill, J T; Brown, K R

2010-01-01

The Hamiltonian control of n qubits requires precision control of both the strength and timing of interactions. Compensation pulses relax the precision requirements by reducing unknown but systematic errors. Using composite pulse techniques designed for single qubits, we show that systematic errors for n-qubit systems can be corrected to arbitrary accuracy given either two non-commuting control Hamiltonians with identical systematic errors or one error-free control Hamiltonian. We also examine composite pulses in the context of quantum computers controlled by two-qubit interactions. For quantum computers based on the XY interaction, single-qubit composite pulse sequences naturally correct systematic errors. For quantum computers based on the Heisenberg or exchange interaction, the composite pulse sequences reduce the logical single-qubit gate errors but increase the errors for logical two-qubit gates.

The impact of measurement errors in the identification of regulatory networks

Directory of Open Access Journals (Sweden)

Sato João R

2009-12-01

Full Text Available Abstract Background There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent and non-time series (independent data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models and dependent (autoregressive models data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error. The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Passive quantum error correction of linear optics networks through error averaging

Science.gov (United States)

Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.

2018-02-01

We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.

Securing Relay Networks with Artificial Noise: An Error Performance-Based Approach

Directory of Open Access Journals (Sweden)

Ying Liu

2017-07-01

Full Text Available We apply the concept of artificial and controlled interference in a two-hop relay network with an untrusted relay, aiming at enhancing the wireless communication secrecy between the source and the destination node. In order to shield the square quadrature amplitude-modulated (QAM signals transmitted from the source node to the relay, the destination node designs and transmits artificial noise (AN symbols to jam the relay reception. The objective of our considered AN design is to degrade the error probability performance at the untrusted relay, for different types of channel state information (CSI at the destination. By considering perfect knowledge of the instantaneous CSI of the source-to-relay and relay-to-destination links, we first present an analytical expression for the symbol error rate (SER performance at the relay. Based on the assumption of an average power constraint at the destination node, we then derive the optimal phase and power distribution of the AN that maximizes the SER at the relay. Furthermore, we obtain the optimal AN design for the case where only statistical CSI is available at the destination node. For both cases, our study reveals that the Gaussian distribution is generally not optimal to generate AN symbols. The presented AN design takes into account practical parameters for the communication links, such as QAM signaling and maximum likelihood decoding.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Science.gov (United States)

Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut

2016-01-01

Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Directory of Open Access Journals (Sweden)

Waddah Waheeb

Full Text Available Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN and the Dynamic Ridge Polynomial Neural Network (DRPNN. Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Us Knows Us in the UK : On Director Networks and CEO Compensation

NARCIS (Netherlands)

Renneboog, L.D.R.; Zhao, Y.

2011-01-01

We analyze the relation between CEO compensation and networks of executive and non-executive directors for all listed UK companies over the period 1996-2007. We examine whether networks are built for reasons of information gathering or for the accumulation of managerial influence. Both indirect

Principle and Design of a Single-phase Inverter-Based Grounding System for Neutral-to-ground Voltage Compensation in Distribution Networks

DEFF Research Database (Denmark)

Wang, Wen; Yan, Lingjie; Zeng, Xiangjun

2017-01-01

Neutral-to-ground overvoltage may occur in non-effectively grounded power systems because of the distributed parameters asymmetry and resonance between Petersen coil and distributed capacitances. Thus, the constraint of neutral-to-ground voltage is critical for the safety of distribution networks....... In this paper, an active grounding system based on single-phase inverter and its control parameter design method is proposed to achieve this objective. Relationship between its output current and neutral-to-ground voltage is derived to explain the principle of neutral-to-ground voltage compensation. Then...

An Experimental Study of Medical Error Explanations: Do Apology, Empathy, Corrective Action, and Compensation Alter Intentions and Attitudes?

Science.gov (United States)

Nazione, Samantha; Pace, Kristin

2015-01-01

Medical malpractice lawsuits are a growing problem in the United States, and there is much controversy regarding how to best address this problem. The medical error disclosure framework suggests that apologizing, expressing empathy, engaging in corrective action, and offering compensation after a medical error may improve the provider-patient relationship and ultimately help reduce the number of medical malpractice lawsuits patients bring to medical providers. This study provides an experimental examination of the medical error disclosure framework and its effect on amount of money requested in a lawsuit, negative intentions, attitudes, and anger toward the provider after a medical error. Results suggest empathy may play a large role in providing positive outcomes after a medical error.

An adaptive angle-doppler compensation method for airborne bistatic radar based on PAST

Science.gov (United States)

Hang, Xu; Jun, Zhao

2018-05-01

Adaptive angle-Doppler compensation method extract the requisite information based on the data itself adaptively, thus avoiding the problem of performance degradation caused by inertia system error. However, this method requires estimation and egiendecomposition of sample covariance matrix, which has a high computational complexity and limits its real-time application. In this paper, an adaptive angle Doppler compensation method based on projection approximation subspace tracking (PAST) is studied. The method uses cyclic iterative processing to quickly estimate the positions of the spectral center of the maximum eigenvector of each range cell, and the computational burden of matrix estimation and eigen-decompositon is avoided, and then the spectral centers of all range cells is overlapped by two dimensional compensation. Simulation results show the proposed method can effectively reduce the no homogeneity of airborne bistatic radar, and its performance is similar to that of egien-decomposition algorithms, but the computation load is obviously reduced and easy to be realized.

Re-Planning for Compensator-Based IMRT with Original Compensators

International Nuclear Information System (INIS)

Zhang, Geoffrey; Feygelman, Vladimir; Stevens, Craig; Li Weiqi; Leuthold, Susan; Springett, Gregory; Hoffe, Sarah

2011-01-01

Compared with multileaf collimator (MLC)-based intensity-modulated radiotherapy (IMRT) for moving targets, compensator-based IMRT has advantages such as shorter beam-on time, fewer monitor units with potentially decreased secondary carcinogenesis risk, better optimization-to-deliverable dose conversion, and often better dose conformity. Some of the disadvantages include additional time for the compensators to be built and delivered, as well as extra cost. Patients undergoing treatment of abdominal cancers often experience weight loss. It would be necessary to account for this change in weight with a new plan and a second set of compensators. However, this would result in treatment delays and added costs. We have developed a method to re-plan the patient using the same set of compensators. Because the weight changes seen with the treatment of abdominal cancers are usually relatively small, a new 4D computed tomography (CT) acquired in the treatment position with markers on the original isocenter tattoos can be registered to the original planning scan. The contours of target volumes from the original scans are copied to the new scan after fusion. The original compensator set can be used together with a few field-in-field (FiF) beams defined by the MLC (or beams with cerrobend blocks for accelerators not equipped with a MLC). The weights of the beams with compensators are reduced so that the FiF or blocked beams can be optimized to mirror the original plan and dose distribution. Seven abdominal cancer cases are presented using this technique. The new plan on the new planning CT images usually has the same dosimetric quality as the original. The target coverage and dose uniformity are improved compared with the plan without FiF/block modification. Techniques combining additional FiF or blocked beams with the original compensators optimize the treatment plans when patients lose weight and save time and cost compared with generating plans with a new set of compensators.

Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

DEFF Research Database (Denmark)

Christiansen, Niels H.; Voie, Per Erlend Torbergsen; Winther, Ole

2014-01-01

Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure...

Error performance analysis in downlink cellular networks with interference management

KAUST Repository

Afify, Laila H.

2015-05-01

Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

Efficient Reactive Power Compensation Algorithm for Distribution Network

Directory of Open Access Journals (Sweden)

J. Jerome

2017-12-01

Full Text Available The use of automation and energy efficient equipment with electronic control would greatly improve industrial production.  These new devices are more sensitive to supply voltage deviation and the characteristics of the power system that was previously ignored are now very important. Hence the benefits of distribution automation have been widely acknowledged in recent years. This paper proposes an efficient load flow solution technique extended to find optimum location for reactive power compensation and network reconfiguration for planning and day-to-day operation of distribution networks.  This is required as a part of the distribution automation system (DAS for taking various control and operation decisions.  The method exploits the radial nature of the network and uses forward and backward propagation technique to calculate branch currents and node voltages.  The proposed method has been tested to analyze several practical distribution networks of various voltage levels and also having high R/X ratio.

Capacity of oscillatory associative-memory networks with error-free retrieval

International Nuclear Information System (INIS)

Nishikawa, Takashi; Lai Yingcheng; Hoppensteadt, Frank C.

2004-01-01

Networks of coupled periodic oscillators (similar to the Kuramoto model) have been proposed as models of associative memory. However, error-free retrieval states of such oscillatory networks are typically unstable, resulting in a near zero capacity. This puts the networks at disadvantage as compared with the classical Hopfield network. Here we propose a simple remedy for this undesirable property and show rigorously that the error-free capacity of our oscillatory, associative-memory networks can be made as high as that of the Hopfield network. They can thus not only provide insights into the origin of biological memory, but can also be potentially useful for applications in information science and engineering

A proportional integral estimator-based clock synchronization protocol for wireless sensor networks.

Science.gov (United States)

Yang, Wenlun; Fu, Minyue

2017-11-01

Clock synchronization is an issue of vital importance in applications of WSNs. This paper proposes a proportional integral estimator-based protocol (EBP) to achieve clock synchronization for wireless sensor networks. As each local clock skew gradually drifts, synchronization accuracy will decline over time. Compared with existing consensus-based approaches, the proposed synchronization protocol improves synchronization accuracy under time-varying clock skews. Moreover, by restricting synchronization error of clock skew into a relative small quantity, it could reduce periodic re-synchronization frequencies. At last, a pseudo-synchronous implementation for skew compensation is introduced as synchronous protocol is unrealistic in practice. Numerical simulations are shown to illustrate the performance of the proposed protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Static compensators (STATCOMs) in power systems

CERN Document Server

Shahnia, Farhad; Ghosh, Arindam

2014-01-01

A static compensator (STATCOM), also known as static synchronous compensator, is a member of the flexible alternating current transmission system (FACTS) devices. It is a power-electronics based regulating device which is composed of a voltage source converter (VSC) and is shunt-connected to alternating current electricity transmission and distribution networks. The voltage source is created from a DC capacitor and the STATCOM can exchange reactive power with the network. It can also supply some active power to the network, if a DC source of power is connected across the capacitor. A STATCOM

Improving material removal determinacy based on the compensation of tool influence function

Science.gov (United States)

Zhong, Bo; Chen, Xian-hua; Deng, Wen-hui; Zhao, Shi-jie; Zheng, Nan

2018-03-01

In the process of computer-controlled optical surfacing (CCOS), the key of correcting the surface error of optical components is to ensure the consistency between the simulated tool influence function and the actual tool influence function (TIF). The existing removal model usually adopts the fixed-point TIF to remove the material with the planning path and velocity, and it considers that the polishing process is linear and time invariant. However, in the actual polishing process, the TIF is a function related to the feed speed. In this paper, the relationship between the actual TIF and the feed speed (i.e. the compensation relationship between static removal and dynamic removal) is determined by experimental method. Then, the existing removal model is modified based on the compensation relationship, to improve the conformity between simulated and actual processing. Finally, the surface error modification correction test are carried out. The results show that the fitting degree of the simulated surface and the experimental surface is better than 88%, and the surface correction accuracy can be better than 1/10 λ (Λ=632.8nm).

Amelioration of Electrical Power Quality based on Modulated Power Filter Compensator

Directory of Open Access Journals (Sweden)

Karrar Hameed Kadhim

2017-08-01

Full Text Available This paper deals with the performance of modeling and implementation of Modulated Power Filter Compensator ( MPFC based on synchronous generator to enhance Electrical Power Quality (EPQ performance , rectification power factor , voltage fixity and decreasing transmission line losses for 300 km transmission line . In this paper (MPFC sketch attendants for intelligent network stability and optimum exploitation. The proposal Flexible AC Transmission Systems ( FACTS can be expanded to distributed renewable energy interface and exploitation systems and also will be easy to modify for voltage fixity, Achieve the required stability, perfect usage and Compensation requirements. MATLAB SIMLINK version R2009b were used as a model of (MPFC.

Roll and pitch set-up errors during volumetric modulated arc delivery: can adapting gantry and collimator angles compensate?

Science.gov (United States)

Hoffmans-Holtzer, Nienke A; Hoffmans, Daan; Dahele, Max; Slotman, Ben J; Verbakel, Wilko F A R

2015-03-01

The purpose of this work was to investigate whether adapting gantry and collimator angles can compensate for roll and pitch setup errors during volumetric modulated arc therapy (VMAT) delivery. Previously delivered clinical plans for locally advanced head-and-neck (H&N) cancer (n = 5), localized prostate cancer (n = 2), and whole brain with simultaneous integrated boost to 5 metastases (WB + 5M, n = 1) were used for this study. Known rigid rotations were introduced in the planning CT scans. To compensate for these, in-house software was used to adapt gantry and collimator angles in the plan. Doses to planning target volumes (PTV) and critical organs at risk (OAR) were calculated with and without compensation and compared with the original clinical plan. Measurements in the sagittal plane in a polystyrene phantom using radiochromic film were compared by gamma (γ) evaluation for 2 H&N cancer patients. For H&N plans, the introduction of 2°-roll and 3°-pitch rotations reduced mean PTV coverage from 98.7 to 96.3%. This improved to 98.1% with gantry and collimator compensation. For prostate plans respective figures were 98.4, 97.5, and 98.4%. For WB + 5M, compensation worked less well, especially for smaller volumes and volumes farther from the isocenter. Mean comparative γ evaluation (3%, 1 mm) between original and pitched plans resulted in 86% γ plan restored the mean comparison to 96% γ < 1. Preliminary data suggest that adapting gantry and collimator angles is a promising way to correct roll and pitch set-up errors of < 3° during VMAT for H&N and prostate cancer.

SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

International Nuclear Information System (INIS)

Kalet, A; Phillips, M; Gennari, J

2014-01-01

Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the

SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

Energy Technology Data Exchange (ETDEWEB)

Kalet, A; Phillips, M; Gennari, J [UniversityWashington, Seattle, WA (United States)

2014-06-01

Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the

High Precision Infrared Temperature Measurement System Based on Distance Compensation

Directory of Open Access Journals (Sweden)

Chen Jing

2017-01-01

Full Text Available To meet the need of real-time remote monitoring of human body surface temperature for optical rehabilitation therapy, a non-contact high-precision real-time temperature measurement method based on distance compensation was proposed, and the system design was carried out. The microcontroller controls the infrared temperature measurement module and the laser range module to collect temperature and distance data. The compensation formula of temperature with distance wass fitted according to the least square method. Testing had been performed on different individuals to verify the accuracy of the system. The results indicate that the designed non-contact infrared temperature measurement system has a residual error of less than 0.2°C and the response time isless than 0.1s in the range of 0 to 60cm. This provides a reference for developing long-distance temperature measurement equipment in optical rehabilitation therapy.

Wireless Sensor Network Localization Research

OpenAIRE

Liang Xin

2014-01-01

DV-Hop algorithm is one of the important range-free localization algorithms. It performs better in isotropic density senor networks, however, it brings larger location errors in random distributed networks. According to the localization principle of the DV-Hop algorithm, this paper improves the estimation of average single hop distance by using the Least Equal Square Error, and revises the estimated distance between the unknown node and the anchor node with compensation coefficient considerin...

The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

KAUST Repository

Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2015-01-01

Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstracts many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this paper, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.

The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

KAUST Repository

Afify, Laila H.

2015-08-18

Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstracts many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this paper, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.

Optimization of the Compensation of a Meshed MV Network by a Modified Genetic Algorithm

DEFF Research Database (Denmark)

Nielsen, Hans; Paar, M.; Toman, P.

2007-01-01

The article discusses the utilization of a modified genetic algorithm (GA) for the optimization of the shunt compensation in meshed and radial MV distribution networks. The algorithm looks for minimum costs of the network power losses and minimum capital and operating costs of applied capacitors......, all of this under limitations specified by a multicriteria penalization function. The parallel evolution branches in the GA are used for the purpose of the optimization accelaration. The application of this GA has been implemented in Matlab. The evaluation part of the GA implementation is based...... on the steady-state analysis using a linear one-line diagram model of a power network. The results of steady-state solutions are compared with the results from the DIgSILENT PowerFactory program. Its practical applicability is demonstrated on examples of 22 kV and meshed overhead distribution networks....

Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement

Science.gov (United States)

Yang, Juqing; Wang, Dayong; Fan, Baixing; Dong, Dengfeng; Zhou, Weihu

2017-03-01

In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot's actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.

Losses compensation; Compensation des pertes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

One mission of RTE (Electric Power Transportation), is to watch over the losses compensation resulting from the power transport on the electric power network. Since january 2001, RTE makes good the electric losses by the purchase of energy. To choose the marketers, a consultation has been realized by RTE. This document presents the rules concerning these losses compensation. (A.L.B.)

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

Directory of Open Access Journals (Sweden)

Hesham Mostafa

2017-09-01

Full Text Available Artificial neural networks (ANNs trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

Science.gov (United States)

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

Random and Systematic Errors Share in Total Error of Probes for CNC Machine Tools

Directory of Open Access Journals (Sweden)

Adam Wozniak

2018-03-01

Full Text Available Probes for CNC machine tools, as every measurement device, have accuracy limited by random errors and by systematic errors. Random errors of these probes are described by a parameter called unidirectional repeatability. Manufacturers of probes for CNC machine tools usually specify only this parameter, while parameters describing systematic errors of the probes, such as pre-travel variation or triggering radius variation, are used rarely. Systematic errors of the probes, linked to the differences in pre-travel values for different measurement directions, can be corrected or compensated, but it is not a widely used procedure. In this paper, the share of systematic errors and random errors in total error of exemplary probes are determined. In the case of simple, kinematic probes, systematic errors are much greater than random errors, so compensation would significantly reduce the probing error. Moreover, it shows that in the case of kinematic probes commonly specified unidirectional repeatability is significantly better than 2D performance. However, in the case of more precise strain-gauge probe systematic errors are of the same order as random errors, which means that errors correction or compensation, in this case, would not yield any significant benefits.

Compressed sensing techniques for receiver based post-compensation of transmitter's nonlinear distortions in OFDM systems

KAUST Repository

Owodunni, Damilola S.

2014-04-01

In this paper, compressed sensing techniques are proposed to linearize commercial power amplifiers driven by orthogonal frequency division multiplexing signals. The nonlinear distortion is considered as a sparse phenomenon in the time-domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional compressed sensing approach, while the second incorporates a priori information about the distortions to enhance the estimation. Finally, the third technique involves an iterative data-aided algorithm that does not require any pilot carriers and hence allows the system to work at maximum bandwidth efficiency. The performances of all the proposed techniques are evaluated on a commercial power amplifier and compared. The error vector magnitude and symbol error rate results show the ability of compressed sensing to compensate for the amplifier\\'s nonlinear distortions. © 2013 Elsevier B.V.

Error compensation of IQ modulator using two-dimensional DFT

Energy Technology Data Exchange (ETDEWEB)

Ohshima, Takashi, E-mail: ohshima@spring8.or.jp [RIKEN, 1-1-1, Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Maesaka, Hirokazu [RIKEN, 1-1-1, Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Matsubara, Shinichi [Japan Synchrotron Radiation Institute, 1-1-1, Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Otake, Yuji [RIKEN, 1-1-1, Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan)

2016-06-01

It is important to precisely set and keep the phase and amplitude of an rf signal in the accelerating cavity of modern accelerators, such as an X-ray Free Electron Laser (XFEL) linac. In these accelerators an acceleration rf signal is generated or detected by an In-phase and Quadrature (IQ) modulator, or a demodulator. If there are any deviations of the phase and the amplitude from the ideal values, crosstalk between the phase and the amplitude of the output signal of the IQ modulator or the demodulator arises. This causes instability of the feedback controls that simultaneously stabilize both the rf phase and the amplitude. To compensate for such deviations, we developed a novel compensation method using a two-dimensional Discrete Fourier Transform (DFT). Because the observed deviations of the phase and amplitude of an IQ modulator involve sinusoidal and polynomial behaviors on the phase angle and the amplitude of the rf vector, respectively, the DFT calculation with these basis functions makes a good approximation with a small number of compensation coefficients. Also, we can suppress high-frequency noise components arising when we measure the deviation data. These characteristics have advantages compared to a Look Up Table (LUT) compensation method. The LUT method usually demands many compensation elements, such as about 300, that are not easy to treat. We applied the DFT compensation method to the output rf signal of a C-band IQ modulator at SACLA, which is an XFEL facility in Japan. The amplitude deviation of the IQ modulator after the DFT compensation was reduced from 15.0% at the peak to less than 0.2% at the peak for an amplitude control range of from 0.1 V to 0.9 V (1.0 V full scale) and for a phase control range from 0 degree to 360 degrees. The number of compensation coefficients is 60, which is smaller than that of the LUT method, and is easy to treat and maintain.

Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

Science.gov (United States)

Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

2009-10-01

A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.

Adaptive control of nonlinear system using online error minimum neural networks.

Science.gov (United States)

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

Directory of Open Access Journals (Sweden)

Zhe Dong

2014-02-01

Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

Social aspects of clinical errors.

Science.gov (United States)

Richman, Joel; Mason, Tom; Mason-Whitehead, Elizabeth; McIntosh, Annette; Mercer, Dave

2009-08-01

Clinical errors, whether committed by doctors, nurses or other professions allied to healthcare, remain a sensitive issue requiring open debate and policy formulation in order to reduce them. The literature suggests that the issues underpinning errors made by healthcare professionals involve concerns about patient safety, professional disclosure, apology, litigation, compensation, processes of recording and policy development to enhance quality service. Anecdotally, we are aware of narratives of minor errors, which may well have been covered up and remain officially undisclosed whilst the major errors resulting in damage and death to patients alarm both professionals and public with resultant litigation and compensation. This paper attempts to unravel some of these issues by highlighting the historical nature of clinical errors and drawing parallels to contemporary times by outlining the 'compensation culture'. We then provide an overview of what constitutes a clinical error and review the healthcare professional strategies for managing such errors.

Interdependency control : compensation strategies for the inherent vulnerability of critical infrastructure networks

International Nuclear Information System (INIS)

Mao, D.; Sotoodeh, M.; Monu, K.; Marti, J.R.; Srivastava, K.D.

2009-01-01

Today's increasingly interacting national critical infrastructures (NCIs) can tolerate most stochastic local disturbances. However, they are extremely fragile under global disturbances, as the latter may either push the whole system into a critical state or reveal many unexpected hidden interdependencies, inducing or triggering cascading failures among all possible layers. This robust yet fragile duality is an inherent vulnerability of modern infrastructures. It is therefore expected that weather-related disasters will be more frequent under a changing climate. This paper proposed an interdependency control strategy (ICS) that would maintain the survival of the most critical services, and compensate for this inherent vulnerability during emergency states. The paper also proposed a generalized adjacency matrix (GAM) to represent the physical interdependencies intra/inter of various infrastructure networks. The vulnerable section in the network can be identified, based on computed results of GAM, number of islands in the network, and influence domain(s) of each component. These features render ICS more effective and convincing. Last, the paper proposed a survivability index for isolated sub-networks and described relevant measures for improving this index during the four phases of emergency management. It was concluded that the proposed strategy is an effective means to reduce the inherent vulnerability and increase the resiliency of these critical infrastructures networks. 20 refs., 5 figs

Double-Frame Current Control with a Multivariable PI Controller and Power Compensation for Weak Unbalanced Networks

CERN Document Server

Siemaszko, Daniel

2015-06-15

The handling of weak networks with asymmetric loads and disturbances im- plies the accurate handling of the second-harmonic component that appears in an unbalanced network. This paper proposes a classic vector control approach using a PI-based controller with superior decoupling capabilities for operation in weak networks with unbalanced phase voltages. A synchronization method for weak unbalanced networks is detailed, with dedicated dimensioning rules. The use of a double-frame controller allows a current symmetry or controlled imbalance to be forced for compensation of power oscillations by controlling the negative current sequence. This paper also serves as a useful reminder of the proper way to cancel the inherent coupling effect due to the transformation to the synchronous rotating reference frame, and of basic considerations of the relationship between switching frequency and control bandwidth.

Equidistant Linear Network Codes with maximal Error-protection from Veronese Varieties

DEFF Research Database (Denmark)

Hansen, Johan P.

2012-01-01

Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possible altered vectorspace. Ralf Koetter and Frank R. Kschischang in Coding for errors and erasures in random network coding (IEEE Transactions on Information Theory...... construct explicit families of vector-spaces of constant dimension where any pair of distinct vector-spaces are equidistant in the above metric. The parameters of the resulting linear network codes which have maximal error-protection are determined....

Fast high resolution ADC based on the flash type with a special error correcting technique

Energy Technology Data Exchange (ETDEWEB)

Xiao-Zhong, Liang; Jing-Xi, Cao [Beijing Univ. (China). Inst. of Atomic Energy

1984-03-01

A fast 12 bits ADC based on the flash type with a simple special error correcting technique which can effectively compensate the level drift of the discriminators and the droop of the stretcher voltage is described. The DNL is comparable with the Wilkinson's ADC and long term drift is far better than its.

A modified backpropagation algorithm for training neural networks on data with error bars

International Nuclear Information System (INIS)

Gernoth, K.A.; Clark, J.W.

1994-08-01

A method is proposed for training multilayer feedforward neural networks on data contaminated with noise. Specifically, we consider the case that the artificial neural system is required to learn a physical mapping when the available values of the target variable are subject to experimental uncertainties, but are characterized by error bars. The proposed method, based on maximum likelihood criterion for parameter estimation, involves simple modifications of the on-line backpropagation learning algorithm. These include incorporation of the error-bar assignments in a pattern-specific learning rate, together with epochal updating of a new measure of model accuracy that replaces the usual mean-square error. The extended backpropagation algorithm is successfully tested on two problems relevant to the modelling of atomic-mass systematics by neural networks. Provided the underlying mapping is reasonably smooth, neural nets trained with the new procedure are able to learn the true function to a good approximation even in the presence of high levels of Gaussian noise. (author). 26 refs, 2 figs, 5 tabs

A Novel Adaptive Joint Time Frequency Algorithm by the Neural Network for the ISAR Rotational Compensation

Directory of Open Access Journals (Sweden)

Zisheng Wang

2018-02-01

Full Text Available We propose a novel adaptive joint time frequency algorithm combined with the neural network (AJTF-NN to focus the distorted inverse synthetic aperture radar (ISAR image. In this paper, a coefficient estimator based on the artificial neural network (ANN is firstly developed to solve the time-consuming rotational motion compensation (RMC polynomial phase coefficient estimation problem. The training method, the cost function and the structure of ANN are comprehensively discussed. In addition, we originally propose a method to generate training dataset sourcing from the ISAR signal models with randomly chosen motion characteristics. Then, prediction results of the ANN estimator is used to directly compensate the ISAR image, or to provide a more accurate initial searching range to the AJTF for possible low-performance scenarios. Finally, some simulation models including the ideal point scatterers and a realistic Airbus A380 are employed to comprehensively investigate properties of the AJTF-NN, such as the stability and the efficiency under different signal-to-noise ratios (SNRs. Results show that the proposed method is much faster than other prevalent improved searching methods, the acceleration ratio are even up to 424 times without the deterioration of compensated image quality. Therefore, the proposed method is potential to the real-time application in the RMC problem of the ISAR imaging.

Improvement of vector compensation method for vehicle magnetic distortion field

Energy Technology Data Exchange (ETDEWEB)

Pang, Hongfeng, E-mail: panghongfeng@126.com; Zhang, Qi; Li, Ji; Luo, Shitu; Chen, Dixiang; Pan, Mengchun; Luo, Feilu

2014-03-15

Magnetic distortions such as eddy-current field and low frequency magnetic field have not been considered in vector compensation methods. A new compensation method is proposed to suppress these magnetic distortions and improve compensation performance, in which the magnetic distortions related to measurement vectors and time are considered. The experimental system mainly consists of a three-axis fluxgate magnetometer (DM-050), an underwater vehicle and a proton magnetometer, in which the scalar value of magnetic field is obtained with the proton magnetometer and considered to be the true value. Comparing with traditional compensation methods, experimental results show that the magnetic distortions can be further reduced by two times. After compensation, error intensity and RMS error are reduced from 11684.013 nT and 7794.604 nT to 16.219 nT and 5.907 nT respectively. It suggests an effective way to improve the compensation performance of magnetic distortions. - Highlights: • A new vector compensation method is proposed for vehicle magnetic distortion. • The proposed model not only includes magnetometer error but also considers magnetic distortion. • Compensation parameters are computed directly by solving nonlinear equations. • Compared with traditional methods, the proposed method is not related with rotation angle rate. • Error intensity and RMS error can be reduced to 1/2 of the error with traditional methods.

Improvement of vector compensation method for vehicle magnetic distortion field

International Nuclear Information System (INIS)

Pang, Hongfeng; Zhang, Qi; Li, Ji; Luo, Shitu; Chen, Dixiang; Pan, Mengchun; Luo, Feilu

2014-01-01

Magnetic distortions such as eddy-current field and low frequency magnetic field have not been considered in vector compensation methods. A new compensation method is proposed to suppress these magnetic distortions and improve compensation performance, in which the magnetic distortions related to measurement vectors and time are considered. The experimental system mainly consists of a three-axis fluxgate magnetometer (DM-050), an underwater vehicle and a proton magnetometer, in which the scalar value of magnetic field is obtained with the proton magnetometer and considered to be the true value. Comparing with traditional compensation methods, experimental results show that the magnetic distortions can be further reduced by two times. After compensation, error intensity and RMS error are reduced from 11684.013 nT and 7794.604 nT to 16.219 nT and 5.907 nT respectively. It suggests an effective way to improve the compensation performance of magnetic distortions. - Highlights: • A new vector compensation method is proposed for vehicle magnetic distortion. • The proposed model not only includes magnetometer error but also considers magnetic distortion. • Compensation parameters are computed directly by solving nonlinear equations. • Compared with traditional methods, the proposed method is not related with rotation angle rate. • Error intensity and RMS error can be reduced to 1/2 of the error with traditional methods

Stabilization of model-based networked control systems

Energy Technology Data Exchange (ETDEWEB)

Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)

2016-06-08

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

Science.gov (United States)

Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

2017-09-01

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

Directory of Open Access Journals (Sweden)

Tat-Bao-Thien Nguyen

2014-01-01

Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

Extending Lifetime of Wireless Sensor Networks using Forward Error Correction

DEFF Research Database (Denmark)

Donapudi, S U; Obel, C O; Madsen, Jan

2006-01-01

Communication between nodes in wireless sensor networks (WSN) is susceptible to transmission errors caused by low signal strength or interference. These errors manifest themselves as lost or corrupt packets. This often leads to retransmission, which in turn results in increased power consumption...

Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Bima Sena Bayu Dewantara

2014-12-01

Full Text Available Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time. Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm

Optical design and studies of a tiled single grating pulse compressor for enhanced parametric space and compensation of tiling errors

Science.gov (United States)

Daiya, D.; Patidar, R. K.; Sharma, J.; Joshi, A. S.; Naik, P. A.; Gupta, P. D.

2017-04-01

A new optical design of tiled single grating pulse compressor has been proposed, set-up and studied. The parametric space, i.e. the laser beam diameters that can be accommodated in the pulse compressor for the given range of compression lengths, has been calculated and shown to have up to two fold enhancement in comparison to our earlier proposed optical designs. The new optical design of the tiled single grating pulse compressor has an additional advantage of self compensation of various tiling errors like longitudinal and lateral piston, tip and groove density mismatch, compared to the earlier designs. Experiments have been carried out for temporal compression of 650 ps positively chirped laser pulses, at central wavelength 1054 nm, down to 235 fs in the tiled grating pulse compressor set up with the proposed design. Further, far field studies have been performed to show the desired compensation of the tiling errors takes place in the new compressor.

Stock-based Compensation Plans and Employee Incentives

OpenAIRE

Jan Zabojnik

2014-01-01

Standard principal-agent theory predicts that large firms should not use employee stock options and other stock-based compensation to provide incentives to non-executive employees. Yet, business practitioners appear to believe that stock-based compensation improves incentives, and mounting empirical evidence points to the same conclusion. This paper provides an explanation for why stock-based incentives can be effective. In the model of this paper, employee stock options complement individual...

The PoET (Prevention of Error-Based Transfers) Project.

Science.gov (United States)

Oliver, Jill; Chidwick, Paula

2017-01-01

The PoET (Prevention of Error-based Transfers) Project is one of the Ethics Quality Improvement Projects (EQIPs) taking place at William Osler Health System. This specific project is designed to reduce transfers from long-term care to hospital that are caused by legal and ethical errors related to consent, capacity and substitute decision-making. The project is currently operating in eight long-term care homes in the Central West Local Health Integration Network and has seen a 56% reduction in multiple transfers before death in hospital.

Volterra Filtering for ADC Error Correction

Directory of Open Access Journals (Sweden)

J. Saliga

2001-09-01

Full Text Available Dynamic non-linearity of analog-to-digital converters (ADCcontributes significantly to the distortion of digitized signals. Thispaper introduces a new effective method for compensation such adistortion based on application of Volterra filtering. Considering ana-priori error model of ADC allows finding an efficient inverseVolterra model for error correction. Efficiency of proposed method isdemonstrated on experimental results.

Bayesian networks modeling for thermal error of numerical control machine tools

Institute of Scientific and Technical Information of China (English)

Xin-hua YAO; Jian-zhong FU; Zi-chen CHEN

2008-01-01

The interaction between the heat source location,its intensity,thermal expansion coefficient,the machine system configuration and the running environment creates complex thermal behavior of a machine tool,and also makes thermal error prediction difficult.To address this issue,a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented.The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques.Due to the effective combination of domain knowledge and sampled data,the BN method could adapt to the change of running state of machine,and obtain satisfactory prediction accuracy.Ex-periments on spindle thermal deformation were conducted to evaluate the modeling performance.Experimental results indicate that the BN method performs far better than the least squares(LS)analysis in terms of modeling estimation accuracy.

Nonlinear bias compensation of ZiYuan-3 satellite imagery with cubic splines

Science.gov (United States)

Cao, Jinshan; Fu, Jianhong; Yuan, Xiuxiao; Gong, Jianya

2017-11-01

Like many high-resolution satellites such as the ALOS, MOMS-2P, QuickBird, and ZiYuan1-02C satellites, the ZiYuan-3 satellite suffers from different levels of attitude oscillations. As a result of such oscillations, the rational polynomial coefficients (RPCs) obtained using a terrain-independent scenario often have nonlinear biases. In the sensor orientation of ZiYuan-3 imagery based on a rational function model (RFM), these nonlinear biases cannot be effectively compensated by an affine transformation. The sensor orientation accuracy is thereby worse than expected. In order to eliminate the influence of attitude oscillations on the RFM-based sensor orientation, a feasible nonlinear bias compensation approach for ZiYuan-3 imagery with cubic splines is proposed. In this approach, no actual ground control points (GCPs) are required to determine the cubic splines. First, the RPCs are calculated using a three-dimensional virtual control grid generated based on a physical sensor model. Second, one cubic spline is used to model the residual errors of the virtual control points in the row direction and another cubic spline is used to model the residual errors in the column direction. Then, the estimated cubic splines are used to compensate the nonlinear biases in the RPCs. Finally, the affine transformation parameters are used to compensate the residual biases in the RPCs. Three ZiYuan-3 images were tested. The experimental results showed that before the nonlinear bias compensation, the residual errors of the independent check points were nonlinearly biased. Even if the number of GCPs used to determine the affine transformation parameters was increased from 4 to 16, these nonlinear biases could not be effectively compensated. After the nonlinear bias compensation with the estimated cubic splines, the influence of the attitude oscillations could be eliminated. The RFM-based sensor orientation accuracies of the three ZiYuan-3 images reached 0.981 pixels, 0.890 pixels, and 1

Spherical aberration compensation method for long focal-length measurement based on Talbot interferometry

Science.gov (United States)

Luo, Yupeng; Huang, Xiao; Bai, Jian; Du, Juan; Liu, Qun; Luo, Yujie; Luo, Jia

2017-08-01

Large-aperture and long focal-length lens is widely used in high energy laser system. The method based on Talbot interferometry is a reliable method to measure the focal length of such elements. By employing divergent beam and two gratings of different periods, this method could realize full-aperture measurement, higher accuracy and better repeatability. However, it does not take into account the spherical aberration of the measured lens resulting in the moiré fringes bending, which will introduce measurement error. Furthermore, in long-focal measurement with divergent beam, this error is an important factor affecting the measurement accuracy. In this paper, we propose a new spherical aberration compensation method, which could significantly reduce the measurement error. Characterized by central-symmetric scanning window, the proposed method is based on the relationship between spherical aberration and the lens aperture. Angle data of moiré fringes in each scanning window is retrieved by Fourier analysis and statistically fitted to estimate a globally optimum value for spherical-aberration-free focal length calculation. Simulation and experiment have been carried out. Compared to the previous work, the proposed method is able to reduce the relative measurement error by 50%. The effect of scanning window size and shift step length on the results is also discussed.

Gain and exposure scheduling to compensate for photorefractive neural-network weight decay

Science.gov (United States)

Goldstein, Adam A.; Petrisor, Gregory C.; Jenkins, B. Keith

1995-03-01

A gain and exposure schedule that theoretically eliminates the effect of photorefractive weight decay for the general class of outer-product neural-network learning algorithms (e.g., backpropagation, Widrow-Hoff, perceptron) is presented. This schedule compensates for photorefractive diffraction-efficiency decay by iteratively increasing the spatial-light-modulator transfer function gain and decreasing the weight-update exposure time. Simulation results for the scheduling procedure, as applied to backpropagation learning for the exclusive-OR problem, show improved learning performance compared with results for networks trained without scheduling.

Neural network decoder for quantum error correcting codes

Science.gov (United States)

Krastanov, Stefan; Jiang, Liang

Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.

A novel approach to error function minimization for feedforward neural networks

International Nuclear Information System (INIS)

Sinkus, R.

1995-01-01

Feedforward neural networks with error backpropagation are widely applied to pattern recognition. One general problem encountered with this type of neural networks is the uncertainty, whether the minimization procedure has converged to a global minimum of the cost function. To overcome this problem a novel approach to minimize the error function is presented. It allows to monitor the approach to the global minimum and as an outcome several ambiguities related to the choice of free parameters of the minimization procedure are removed. (orig.)

Adaptive friction compensation: a globally stable approach

NARCIS (Netherlands)

Verbert, K.A.; Tóth, R.; Babuska, R.

2016-01-01

In this paper, an adaptive friction compensation scheme is proposed. The friction force is computed as a timevarying friction coefficient multiplied by the sign of the velocity and an on-line update law is designed to estimate this coefficient based on the actual position and velocity errors.

Evolution of an artificial neural network based autonomous land vehicle controller.

Science.gov (United States)

Baluja, S

1996-01-01

This paper presents an evolutionary method for creating an artificial neural network based autonomous land vehicle controller. The evolved controllers perform better in unseen situations than those trained with an error backpropagation learning algorithm designed for this task. In this paper, an overview of the previous connectionist based approaches to this task is given, and the evolutionary algorithms used in this study are described in detail. Methods for reducing the high computational costs of training artificial neural networks with evolutionary algorithms are explored. Error metrics specific to the task of autonomous vehicle control are introduced; the evolutionary algorithms guided by these error metrics reveal improved performance over those guided by the standard sum-squared error metric. Finally, techniques for integrating evolutionary search and error backpropagation are presented. The evolved networks are designed to control Carnegie Mellon University's NAVLAB vehicles in road following tasks.

Transfer Error and Correction Approach in Mobile Network

Science.gov (United States)

Xiao-kai, Wu; Yong-jin, Shi; Da-jin, Chen; Bing-he, Ma; Qi-li, Zhou

With the development of information technology and social progress, human demand for information has become increasingly diverse, wherever and whenever people want to be able to easily, quickly and flexibly via voice, data, images and video and other means to communicate. Visual information to the people direct and vivid image, image / video transmission also been widespread attention. Although the third generation mobile communication systems and the emergence and rapid development of IP networks, making video communications is becoming the main business of the wireless communications, however, the actual wireless and IP channel will lead to error generation, such as: wireless channel multi- fading channels generated error and blocking IP packet loss and so on. Due to channel bandwidth limitations, the video communication compression coding of data is often beyond the data, and compress data after the error is very sensitive to error conditions caused a serious decline in image quality.

Methods of In-Process On-Machine Auto-Inspection of Dimensional Error and Auto-Compensation of Tool Wear for Precision Turning

Directory of Open Access Journals (Sweden)

Shih-Ming Wang

2016-04-01

Full Text Available The purpose of this study is mainly to develop an information and communication technology (ICT-based intelligent dimension inspection and tool wear compensation method for precision tuning. With the use of vibration signal processing/characteristics analysis technology combined with ICT, statistical analysis, and diagnosis algorithms, the method can be used to proceed with an on-line dimension inspection and on-machine tool wear auto-compensation for the turning process. Meanwhile, the method can also monitor critical tool life to identify the appropriate time for cutter replacement to reduce machining costs and improve the production efficiency of the turning process. Compared to the traditional ways, the method offers the advantages of requiring less manpower, and having better production efficiency, high tool life, fewer scrap parts, and low costs for inspection instruments. Algorithms and diagnosis threshold values for the detection, cutter wear compensation, and cutter life monitoring were developed. In addition, a bilateral communication module utilizing FANUC Open CNC (computer numerical control Application Programming Interface (API Spec was developed for the on-line extraction of instant NC (numerical control codes for monitoring and transmit commands to CNC controllers for cutter wear compensation. With use of local area networks (LAN to deliver the detection and correction information, the proposed method was able to remotely control the on-machine monitoring process and upload the machining and inspection data to a remote central platform for further production optimization. The verification experiments were conducted on a turning production line. The results showed that the system provided 93% correction for size inspection and 100% correction for cutter wear compensation.

Tensor Networks and Quantum Error Correction

Science.gov (United States)

Ferris, Andrew J.; Poulin, David

2014-07-01

We establish several relations between quantum error correction (QEC) and tensor network (TN) methods of quantum many-body physics. We exhibit correspondences between well-known families of QEC codes and TNs, and demonstrate a formal equivalence between decoding a QEC code and contracting a TN. We build on this equivalence to propose a new family of quantum codes and decoding algorithms that generalize and improve upon quantum polar codes and successive cancellation decoding in a natural way.

Energy Storage Characteristic Analysis of Voltage Sags Compensation for UPQC Based on MMC for Medium Voltage Distribution System

Directory of Open Access Journals (Sweden)

Yongchun Yang

2018-04-01

Full Text Available The modular multilevel converter (MMC, as a new type of voltage source converter, is increasingly used because it is a distributed storage system. There are many advantages of using the topological structure of the MMC on a unified power quality controller (UPQC, and voltage sag mitigation is an important use of the MMC energy storage system for the power quality compensation process. In this paper, based on the analysis of the topology of the MMC, the essence of energy conversion in a UPQC of voltage sag compensation is analyzed; then, the energy storage characteristics are calculated and analyzed to determine the performance index of voltage sag compensation; in addition, the simulation method is used to verify the voltage sag compensation characteristics of the UPQC; finally, an industrial prototype of the UPQC based on an MMC for 10 kV of medium voltage distribution network has been developed, and the basic functions of UPQC have been tested.

APPLICATION OF COMPENSATION METHOD FOR SEPARATION USEFUL SIGNAL AND INTERFERENCE FROM NEARBY SOURCES

Directory of Open Access Journals (Sweden)

2016-01-01

Full Text Available Based on the comparative analysis of the known methods of noise suppression the ratios for the angular measurements are obtained. A mathematical model experiment to estimate the dependence of measurement error on the relative position of interference source and useful signal has been conducted. The modified method of interfer- ence compensation is tested experimentally. The analysis of obtained angular measurements for the considered methods shows that the modified method of compensation allows obtaining more precise estimates. The analyzed methodsallow considerably eliminating the useful signal from the antenna additional channel which reduces errors of angular misalignment.To determine the degree of the radar error analytically is not always possible, and in future comparison of the ef- fectiveness of various methods of interference compensation will be expected to conduct by means of mathematical model-ing of radar closed contour.

Portfolio management fees: assets or profits based compensation?

OpenAIRE

Gil-Bazo, Javier

2001-01-01

This paper compares assets-based portfolio management fees to profits-based fees. Whilst both forms of compensation can provide appropriate risk incentives, fund managers' limited liability induces more excess risk-taking under a profits-based fee contract. On the other hand, an assets-based fee is more costly to investors. In Spain, where the law explicitly permits both forms of retribution, assets-based fees are observed far more frequently. Under this type of compensation, the paper provid...

Lossless Compression of Video using Motion Compensation

DEFF Research Database (Denmark)

Martins, Bo; Forchhammer, Søren

1998-01-01

We investigate lossless coding of video using predictive coding andmotion compensation. The methods incorporate state-of-the-art lossless techniques such ascontext based prediction and bias cancellation, Golomb coding, high resolution motion field estimation,3d-dimensional predictors, prediction...... using one or multiple previous images, predictor dependent error modelling, and selection of motion field by code length. For slow pan or slow zoom sequences, coding methods that use multiple previous images are up to 20% better than motion compensation using a single previous image and up to 40% better...

Analysis and Compensation of Dead-Time Effect of a ZVT PWM Inverter Considering the Rise- and Fall-Times

Directory of Open Access Journals (Sweden)

Hailin Zhang

2016-11-01

Full Text Available The dead-time effect, as an intrinsic problem of the converters based on the half-bridge unit, leads to distortions in the converter output. Although several dead-time effect compensation or elimination methods have been proposed, they cannot fully remove the dead-time effect of blanking delay error, because the output current polarity is difficult detect accurately. This paper utilizes the zero-voltage-switching (ZVT technique to eliminate the blanking delay error, which is the main drawback of the hard-switching inverter, although the technique initially aims to improve the efficiency. A typical ZVT inverter—the auxiliary resonant snubber inverter (ARSI is analyzed. The blanking delay error is completely eliminated in the ARSI. Another error source caused by the finite rise- and fall-times of the voltage is analyzed, which was not considered in the hard-switching inverter. A compensation method based on the voltage error estimation is proposed to compensate the rise- and fall-error. A prototype was developed to verify the effectiveness of the proposed control. Both the simulation and experimental results demonstrate that the qualities of the output current and voltage in the ARSI are better than that in the hard-switching inverter due to the elimination of the blanking delay error. The total harmonic distortion (THD of the output is further reduced by using the proposed compensation method in the ARSI.

NOVEL APPROACH TO IMPROVE GEOCENTRIC TRANSLATION MODEL PERFORMANCE USING ARTIFICIAL NEURAL NETWORK TECHNOLOGY

Directory of Open Access Journals (Sweden)

Yao Yevenyo Ziggah

Full Text Available Abstract: Geocentric translation model (GTM in recent times has not gained much popularity in coordinate transformation research due to its attainable accuracy. Accurate transformation of coordinate is a major goal and essential procedure for the solution of a number of important geodetic problems. Therefore, motivated by the successful application of Artificial Intelligence techniques in geodesy, this study developed, tested and compared a novel technique capable of improving the accuracy of GTM. First, GTM based on official parameters (OP and new parameters determined using the arithmetic mean (AM were applied to transform coordinate from global WGS84 datum to local Accra datum. On the basis of the results, the new parameters (AM attained a maximum horizontal position error of 1.99 m compared to the 2.75 m attained by OP. In line with this, artificial neural network technology of backpropagation neural network (BPNN, radial basis function neural network (RBFNN and generalized regression neural network (GRNN were then used to compensate for the GTM generated errors based on AM parameters to obtain a new coordinate transformation model. The new implemented models offered significant improvement in the horizontal position error from 1.99 m to 0.93 m.

Research on effects of phase error in phase-shifting interferometer

Science.gov (United States)

Wang, Hongjun; Wang, Zhao; Zhao, Hong; Tian, Ailing; Liu, Bingcai

2007-12-01

Referring to phase-shifting interferometry technology, the phase shifting error from the phase shifter is the main factor that directly affects the measurement accuracy of the phase shifting interferometer. In this paper, the resources and sorts of phase shifting error were introduction, and some methods to eliminate errors were mentioned. Based on the theory of phase shifting interferometry, the effects of phase shifting error were analyzed in detail. The Liquid Crystal Display (LCD) as a new shifter has advantage as that the phase shifting can be controlled digitally without any mechanical moving and rotating element. By changing coded image displayed on LCD, the phase shifting in measuring system was induced. LCD's phase modulation characteristic was analyzed in theory and tested. Based on Fourier transform, the effect model of phase error coming from LCD was established in four-step phase shifting interferometry. And the error range was obtained. In order to reduce error, a new error compensation algorithm was put forward. With this method, the error can be obtained by process interferogram. The interferogram can be compensated, and the measurement results can be obtained by four-step phase shifting interferogram. Theoretical analysis and simulation results demonstrate the feasibility of this approach to improve measurement accuracy.

Reference voltage calculation method based on zero-sequence component optimisation for a regional compensation DVR

Science.gov (United States)

Jian, Le; Cao, Wang; Jintao, Yang; Yinge, Wang

2018-04-01

This paper describes the design of a dynamic voltage restorer (DVR) that can simultaneously protect several sensitive loads from voltage sags in a region of an MV distribution network. A novel reference voltage calculation method based on zero-sequence voltage optimisation is proposed for this DVR to optimise cost-effectiveness in compensation of voltage sags with different characteristics in an ungrounded neutral system. Based on a detailed analysis of the characteristics of voltage sags caused by different types of faults and the effect of the wiring mode of the transformer on these characteristics, the optimisation target of the reference voltage calculation is presented with several constraints. The reference voltages under all types of voltage sags are calculated by optimising the zero-sequence component, which can reduce the degree of swell in the phase-to-ground voltage after compensation to the maximum extent and can improve the symmetry degree of the output voltages of the DVR, thereby effectively increasing the compensation ability. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Aeromagnetic Compensation Algorithm Based on Principal Component Analysis

Directory of Open Access Journals (Sweden)

Peilin Wu

2018-01-01

Full Text Available Aeromagnetic exploration is an important exploration method in geophysics. The data is typically measured by optically pumped magnetometer mounted on an aircraft. But any aircraft produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is important in aeromagnetic exploration. However, multicollinearity of the aeromagnetic compensation model degrades the performance of the compensation. To address this issue, a novel aeromagnetic compensation method based on principal component analysis is proposed. Using the algorithm, the correlation in the feature matrix is eliminated and the principal components are using to construct the hyperplane to compensate the platform-generated magnetic fields. The algorithm was tested using a helicopter, and the obtained improvement ratio is 9.86. The compensated quality is almost the same or slightly better than the ridge regression. The validity of the proposed method was experimentally demonstrated.

Compensation of the magnetization current induced sextupole error at LHC injection field by short lumped permanent sextupole magnets, incorporated into the end configuration of superconducting dipoles

CERN Document Server

Asner, A

1985-01-01

Compensation of the magnetization current induced sextupole error at LHC injection field by short lumped permanent sextupole magnets, incorporated into the end configuration of superconducting dipoles

Complex networks-based energy-efficient evolution model for wireless sensor networks

Energy Technology Data Exchange (ETDEWEB)

Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)

2009-08-30

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

Complex networks-based energy-efficient evolution model for wireless sensor networks

International Nuclear Information System (INIS)

Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun

2009-01-01

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

Reliability-Based Marginal Cost Pricing Problem Case with Both Demand Uncertainty and Travelers’ Perception Errors

Directory of Open Access Journals (Sweden)

Shaopeng Zhong

2013-01-01

Full Text Available Focusing on the first-best marginal cost pricing (MCP in a stochastic network with both travel demand uncertainty and stochastic perception errors within the travelers’ route choice decision processes, this paper develops a perceived risk-based stochastic network marginal cost pricing (PRSN-MCP model. Numerical examples based on an integrated method combining the moment analysis approach, the fitting distribution method, and the reliability measures are also provided to demonstrate the importance and properties of the proposed model. The main finding is that ignoring the effect of travel time reliability and travelers’ perception errors may significantly reduce the performance of the first-best MCP tolls, especially under high travelers’ confidence and network congestion levels. The analysis result could also enhance our understanding of (1 the effect of stochastic perception error (SPE on the perceived travel time distribution and the components of road toll; (2 the effect of road toll on the actual travel time distribution and its reliability measures; (3 the effect of road toll on the total network travel time distribution and its statistics; and (4 the effect of travel demand level and the value of reliability (VoR level on the components of road toll.

High Frequency Resonance Damping of DFIG based Wind Power System under Weak Network

DEFF Research Database (Denmark)

Song, Yipeng; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

When operating in a micro or weak grid which has a relatively large network impedance, the Doubly Fed Induction Generator (DFIG) based wind power generation system is prone to suffer high frequency resonance due to the impedance interaction between DFIG system and the parallel compensated network...

Neural network approximation of nonlinearity in laser nano-metrology system based on TLMI

Energy Technology Data Exchange (ETDEWEB)

Olyaee, Saeed; Hamedi, Samaneh, E-mail: s_olyaee@srttu.edu [Nano-photonics and Optoelectronics Research Laboratory (NORLab), Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University (SRTTU), Lavizan, 16788, Tehran (Iran, Islamic Republic of)

2011-02-01

In this paper, an approach based on neural network (NN) for nonlinearity modeling in a nano-metrology system using three-longitudinal-mode laser heterodyne interferometer (TLMI) for length and displacement measurements is presented. We model nonlinearity errors that arise from elliptically and non-orthogonally polarized laser beams, rotational error in the alignment of laser head with respect to the polarizing beam splitter, rotational error in the alignment of the mixing polarizer, and unequal transmission coefficients in the polarizing beam splitter. Here we use a neural network algorithm based on the multi-layer perceptron (MLP) network. The simulation results show that multi-layer feed forward perceptron network is successfully applicable to real noisy interferometer signals.

Neural network approximation of nonlinearity in laser nano-metrology system based on TLMI

International Nuclear Information System (INIS)

Olyaee, Saeed; Hamedi, Samaneh

2011-01-01

In this paper, an approach based on neural network (NN) for nonlinearity modeling in a nano-metrology system using three-longitudinal-mode laser heterodyne interferometer (TLMI) for length and displacement measurements is presented. We model nonlinearity errors that arise from elliptically and non-orthogonally polarized laser beams, rotational error in the alignment of laser head with respect to the polarizing beam splitter, rotational error in the alignment of the mixing polarizer, and unequal transmission coefficients in the polarizing beam splitter. Here we use a neural network algorithm based on the multi-layer perceptron (MLP) network. The simulation results show that multi-layer feed forward perceptron network is successfully applicable to real noisy interferometer signals.

Performance of the Wavelet Transform-Neural Network Based Receiver for DPIM in Diffuse Indoor Optical Wireless Links in Presence of Artificial Light Interference

Directory of Open Access Journals (Sweden)

Sujan Rajbhandari

2009-06-01

Full Text Available Artificial neural network (ANN has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER performance of digital pulse interval modulation (DPIM in diffuse indoor optical wireless (OW links subjected to the artificial light interference (ALI is reported with new receiver structure based on the discrete WT (DWT and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI and ALI.

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

Science.gov (United States)

Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

2018-04-01

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

Science.gov (United States)

Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.

2012-01-01

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

Error-backpropagation in temporally encoded networks of spiking neurons

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractFor a network of spiking neurons that encodes information in the timing of individual spike-times, we derive a supervised learning rule, emph{SpikeProp, akin to traditional error-backpropagation and show how to overcome the discontinuities introduced by thresholding. With this algorithm,

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

Science.gov (United States)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

Ultrasound-based tumor movement compensation during navigated laparoscopic liver interventions.

Science.gov (United States)

Shahin, Osama; Beširević, Armin; Kleemann, Markus; Schlaefer, Alexander

2014-05-01

Image-guided navigation aims to provide better orientation and accuracy in laparoscopic interventions. However, the ability of the navigation system to reflect anatomical changes and maintain high accuracy during the procedure is crucial. This is particularly challenging in soft organs such as the liver, where surgical manipulation causes significant tumor movements. We propose a fast approach to obtain an accurate estimation of the tumor position throughout the procedure. Initially, a three-dimensional (3D) ultrasound image is reconstructed and the tumor is segmented. During surgery, the position of the tumor is updated based on newly acquired tracked ultrasound images. The initial segmentation of the tumor is used to automatically detect the tumor and update its position in the navigation system. Two experiments were conducted. First, a controlled phantom motion using a robot was performed to validate the tracking accuracy. Second, a needle navigation scenario based on pseudotumors injected into ex vivo porcine liver was studied. In the robot-based evaluation, the approach estimated the target location with an accuracy of 0.4 ± 0.3 mm. The mean navigation error in the needle experiment was 1.2 ± 0.6 mm, and the algorithm compensated for tumor shifts up to 38 mm in an average time of 1 s. We demonstrated a navigation approach based on tracked laparoscopic ultrasound (LUS), and focused on the neighborhood of the tumor. Our experimental results indicate that this approach can be used to quickly and accurately compensate for tumor movements caused by surgical manipulation during laparoscopic interventions. The proposed approach has the advantage of being based on the routinely used LUS; however, it upgrades its functionality to estimate the tumor position in 3D. Hence, the approach is repeatable throughout surgery, and enables high navigation accuracy to be maintained.

PERFORMANCE OF OPPORTUNISTIC SPECTRUM ACCESS WITH SENSING ERROR IN COGNITIVE RADIO AD HOC NETWORKS

Directory of Open Access Journals (Sweden)

N. ARMI

2012-04-01

Full Text Available Sensing in opportunistic spectrum access (OSA has a responsibility to detect the available channel by performing binary hypothesis as busy or idle states. If channel is busy, secondary user (SU cannot access and refrain from data transmission. SU is allowed to access when primary user (PU does not use it (idle states. However, channel is sensed on imperfect communication link. Fading, noise and any obstacles existed can cause sensing errors in PU signal detection. False alarm detects idle states as a busy channel while miss-identification detects busy states as an idle channel. False detection makes SU refrain from transmission and reduces number of bits transmitted. On the other hand, miss-identification causes SU collide to PU transmission. This paper study the performance of OSA based on the greedy approach with sensing errors by the restriction of maximum collision probability allowed (collision threshold by PU network. The throughput of SU and spectrum capacity metric is used to evaluate OSA performance and make comparisons to those ones without sensing error as function of number of slot based on the greedy approach. The relations between throughput and signal to noise ratio (SNR with different collision probability as well as false detection with different SNR are presented. According to the obtained results show that CR users can gain the reward from the previous slot for both of with and without sensing errors. It is indicated by the throughput improvement as slot number increases. However, sensing on imperfect channel with sensing errors can degrade the throughput performance. Subsequently, the throughput of SU and spectrum capacity improves by increasing maximum collision probability allowed by PU network as well. Due to frequent collision with PU, the throughput of SU and spectrum capacity decreases at certain value of collision threshold. Computer simulation is used to evaluate and validate these works.

Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

Science.gov (United States)

Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

2015-09-01

To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

The design of multi-lead-compensators for stabilization and pole placement in double-integrator networks

NARCIS (Netherlands)

Wan, Yan; Roy, Sandip; Saberi, Ali; Stoorvogel, Antonie Arij

2010-01-01

We study decentralized controller design for stabilization and pole-placement, in a network of autonomous agents with double-integrator internal dynamics and arbitrary observation topology. We show that a simple multi-lead-compensator architecture, in particular one in which each agent uses a

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network.

Science.gov (United States)

Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

2015-07-24

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Xingming Sun

2015-07-01

Full Text Available Air temperature (AT is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS. Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR. Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

Constrained motion estimation-based error resilient coding for HEVC

Science.gov (United States)

Guo, Weihan; Zhang, Yongfei; Li, Bo

2018-04-01

Unreliable communication channels might lead to packet losses and bit errors in the videos transmitted through it, which will cause severe video quality degradation. This is even worse for HEVC since more advanced and powerful motion estimation methods are introduced to further remove the inter-frame dependency and thus improve the coding efficiency. Once a Motion Vector (MV) is lost or corrupted, it will cause distortion in the decoded frame. More importantly, due to motion compensation, the error will propagate along the motion prediction path, accumulate over time, and significantly degrade the overall video presentation quality. To address this problem, we study the problem of encoder-sider error resilient coding for HEVC and propose a constrained motion estimation scheme to mitigate the problem of error propagation to subsequent frames. The approach is achieved by cutting off MV dependencies and limiting the block regions which are predicted by temporal motion vector. The experimental results show that the proposed method can effectively suppress the error propagation caused by bit errors of motion vector and can improve the robustness of the stream in the bit error channels. When the bit error probability is 10-5, an increase of the decoded video quality (PSNR) by up to1.310dB and on average 0.762 dB can be achieved, compared to the reference HEVC.

Implementation of self-organizing neural networks for visuo-motor control of an industrial robot.

Science.gov (United States)

Walter, J A; Schulten, K I

1993-01-01

The implementation of two neural network algorithms for visuo-motor control of an industrial robot (Puma 562) is reported. The first algorithm uses a vector quantization technique, the ;neural-gas' network, together with an error correction scheme based on a Widrow-Hoff-type learning rule. The second algorithm employs an extended self-organizing feature map algorithm. Based on visual information provided by two cameras, the robot learns to position its end effector without an external teacher. Within only 3000 training steps, the robot-camera system is capable of reducing the positioning error of the robot's end effector to approximately 0.1% of the linear dimension of the work space. By employing adaptive feedback the robot succeeds in compensating not only slow calibration drifts, but also sudden changes in its geometry. Hardware aspects of the robot-camera system are discussed.

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

Directory of Open Access Journals (Sweden)

Ruihong Xie

2017-05-01

Full Text Available This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square error is 1.253 mrad when tracking 10° 0.2 Hz signal.

Time Error Analysis of SOE System Using Network Time Protocol

International Nuclear Information System (INIS)

Keum, Jong Yong; Park, Geun Ok; Park, Heui Youn

2005-01-01

To find the accuracy of time in the fully digitalized SOE (Sequence of Events) system, we used a formal specification of the Network Time Protocol (NTP) Version 3, which is used to synchronize time keeping among a set of distributed computers. Through constructing a simple experimental environments and experimenting internet time synchronization, we analyzed the time errors of local clocks of SOE system synchronized with a time server via computer networks

The effect of TWD estimation error on the geometry of machined surfaces in micro-EDM milling

DEFF Research Database (Denmark)

Puthumana, Govindan; Bissacco, Giuliano; Hansen, Hans Nørgaard

In micro EDM (electrical discharge machining) milling, tool electrode wear must be effectively compensated in order to achieve high accuracy of machined features [1]. Tool wear compensation in micro-EDM milling can be based on off-line techniques with limited accuracy such as estimation...... and statistical characterization of the discharge population [3]. The TWD based approach permits the direct control of the position of the tool electrode front surface. However, TWD estimation errors will generate a self-amplifying error on the tool electrode axial depth during micro-EDM milling. Therefore....... The error propagation effect is demonstrated through a software simulation tool developed by the authors for determination of the correct TWD for subsequent use in compensation of electrode wear in EDM milling. The implemented model uses an initial arbitrary estimation of TWD and a single experiment...

Refractive index sensor based on optical fiber end face using pulse reference-based compensation technique

Science.gov (United States)

Bian, Qiang; Song, Zhangqi; Zhang, Xueliang; Yu, Yang; Chen, Yuzhong

2018-03-01

We proposed a refractive index sensor based on optical fiber end face using pulse reference-based compensation technique. With good compensation effect of this compensation technique, the power fluctuation of light source, the change of optic components transmission loss and coupler splitting ratio can be compensated, which largely reduces the background noise. The refractive index resolutions can achieve 3.8 × 10-6 RIU and1.6 × 10-6 RIU in different refractive index regions.

Three-point method for measuring the geometric error components of linear and rotary axes based on sequential multilateration

International Nuclear Information System (INIS)

Zhang, Zhenjiu; Hu, Hong

2013-01-01

The linear and rotary axes are fundamental parts of multi-axis machine tools. The geometric error components of the axes must be measured for motion error compensation to improve the accuracy of the machine tools. In this paper, a simple method named the three point method is proposed to measure the geometric error of the linear and rotary axes of the machine tools using a laser tracker. A sequential multilateration method, where uncertainty is verified through simulation, is applied to measure the 3D coordinates. Three noncollinear points fixed on the stage of each axis are selected. The coordinates of these points are simultaneously measured using a laser tracker to obtain their volumetric errors by comparing these coordinates with ideal values. Numerous equations can be established using the geometric error models of each axis. The geometric error components can be obtained by solving these equations. The validity of the proposed method is verified through a series of experiments. The results indicate that the proposed method can measure the geometric error of the axes to compensate for the errors in multi-axis machine tools.

Doppler Shift Compensation Schemes in VANETs

Directory of Open Access Journals (Sweden)

F. Nyongesa

2015-01-01

Full Text Available Over the last decade vehicle-to-vehicle (V2V communication has received a lot of attention as it is a crucial issue in intravehicle communication as well as in Intelligent Transportation System (ITS. In ITS the focus is placed on integration of communication between mobile and fixed infrastructure to execute road safety as well as nonsafety information dissemination. The safety application such as emergence alerts lays emphasis on low-latency packet delivery rate (PDR, whereas multimedia and infotainment call for high data rates at low bit error rate (BER. The nonsafety information includes multimedia streaming for traffic information and infotainment applications such as playing audio content, utilizing navigation for driving, and accessing Internet. A lot of vehicular ad hoc network (VANET research has focused on specific areas including channel multiplexing, antenna diversity, and Doppler shift compensation schemes in an attempt to optimize BER performance. Despite this effort few surveys have been conducted to highlight the state-of-the-art collection on Doppler shift compensation schemes. Driven by this cause we survey some of the recent research activities in Doppler shift compensation schemes and highlight challenges and solutions as a stock-taking exercise. Moreover, we present open issues to be further investigated in order to address the challenges of Doppler shift in VANETs.

BAYES-HEP: Bayesian belief networks for estimation of human error probability

International Nuclear Information System (INIS)

Karthick, M.; Senthil Kumar, C.; Paul, Robert T.

2017-01-01

Human errors contribute a significant portion of risk in safety critical applications and methods for estimation of human error probability have been a topic of research for over a decade. The scarce data available on human errors and large uncertainty involved in the prediction of human error probabilities make the task difficult. This paper presents a Bayesian belief network (BBN) model for human error probability estimation in safety critical functions of a nuclear power plant. The developed model using BBN would help to estimate HEP with limited human intervention. A step-by-step illustration of the application of the method and subsequent evaluation is provided with a relevant case study and the model is expected to provide useful insights into risk assessment studies

Adaptive back-stepping control of the harmonic drive system with LuGre model-based friction compensation

Science.gov (United States)

Liu, Sen; Gang, Tieqiang

2018-03-01

Harmonic drives are widely used in aerospace and industrial robots. Flexibility, friction and parameter uncertainty will result in transmission performance degradation. In this paper, an adaptive back-stepping method with friction compensation is proposed to improve the tracking performance of the harmonic drive system. The nonlinear friction is described by LuGre model and compensated with a friction observer, and the uncertainty of model parameters is resolved by adaptive parameter estimation method. By using Lyapunov stability theory, it is proved that all the errors of the closed-loop system are uniformly ultimately bounded. Simulations illustrate the effectiveness of our friction compensation method.

All-optical and digital non-linear compensation algorithms in flex-coherent grouped and un-grouped contiguous spectrum based networks

DEFF Research Database (Denmark)

Asif, Rameez

2016-01-01

We have evaluated that in-line non-linear compensation schemes decrease the complexity of digital backward propagation and enhance the transmission performance of 40/112/224 Gbit/s mixed line rate network. Multiple bit rates, i.e. 40/112/224 Gbit/s and modulation formats (i.e. DP-QPSK and DP-16QAM......) are transmitted over 1280 km of Large $$\\hbox {A}_{eff}$$ A e f f Pure-Silica core fiber. Both grouped and un-grouped spectral allocation schemes are investigated. Optical add-drop multiplexers are used to drop the required wavelength for signal processing in the transmission link. Moreover, hybrid mid...

Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Hina Nasir

2016-07-01

Full Text Available This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs; performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE efficient depth based routing and Enhanced-ACE (E-ACE are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ. E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment.

THE EVALUATION OF THE EFFECT OF REACTIVE POWER COMPENSATION IN ELECTRIC POWER LOSSES IN ELECTRIC NETWORK OF RAILWAY JUNCTION

OpenAIRE

O. I. Bondar; I. L. Bondar

2009-01-01

In this work the generalized mathematical model of an electrical network of the electrified railway junction is proposed. An estimation of influence of static var compensators installation on electric power losses in a network is executed on the basis of given model.

Apparent Power, Expanded Definitions, Transient Operating Conditions, Network Reactions, Compensation, Papers Presented at ETG Conference (Energy Technology Society), 1979

Energy Technology Data Exchange (ETDEWEB)

1980-01-01

The Proceedings of the Conference comprises 12 papers dealing with the following themes: the history of apparent power; active and apparent power of periodical currents in single-phase and multiphase systems with periodical voltages of any shape of curve; power values in unsteady state processes; power and harmonic relations in mains-controlled direct frequency converters; power electronic devices for apparent power compensation; electric arc effects on power system: characteristics, measurement methods, compensation; harmonic compensation by means of impedance wave trap filters in rectifiers; compensation of apparent power by filter circuits; apparent power effects on ac railroad power systems; effects of apparent power in low-voltage networks of public power supply.

A method for calibration of Soleil-Babinet compensator using a spectrophotometer

Science.gov (United States)

Wang, Jun; Chen, Lei; Li, Bo; Shi, Lili; Luo, Ting

2010-06-01

A method using a spectrophotometer for calibrating Soleil-Babinet compensator is proposed. It is based on the spectroscopic method which utilizes the relation between transmittance and wavelength to obtain retardation. By placing a multiple order half wave plate behind the Soleil-Babinet compensator, zero-order retardation can be measured, which is difficult to accomplish by spectroscopic method. In the experiment, the retardations of the compensator in the range 0- λ are measured. It is demonstrated that the precision of retardation is 0.45 nm at the position 0 and λ while the maximum error is less than 1 nm between the two positions.

Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaohu [ORNL; Shi, Di [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Zhiwei [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Huang, Junhui [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Xu [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2017-01-01

Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

Ophthalmic compensation of visual ametropia based on a programmable diffractive lens

Science.gov (United States)

Millán, Maria S.; Pérez-Cabré, Elisabet; Romero, Lenny A.; Ramírez, Natalia

2013-11-01

Pixelated liquid crystal displays have been widely used as spatial light modulators to implement programmable diffractive optical elements (DOEs), particularly diffractive lenses. Many different applications of such components have been developed in information optics and optical processors that take advantage of their properties of great flexibility, easy and fast refreshment, and multiplexing capability in comparison with equivalent conventional refractive lenses. In this paper, we explore the application of programmable diffractive lenses displayed on the pixelated screen of a liquid crystal on silicon spatial light modulator (LCoS-SLM) to ophthalmic optics. In particular, we consider the use of programmable diffractive lenses for the visual compensation of some refractive errors (myopia, hyperopia). The theoretical principles of compensation are described and sketched using geometrical optics and paraxial ray tracing. A series of experiments with artificial eye in optical bench are conducted to analyze the compensation accuracy in terms of optical power and to compare the results with those obtained by means of conventional ophthalmic lenses. Practical considerations oriented to feasible applications are provided.

Z-Source Inverter Based Power Quality Compensator with Enhanced Ride-Through Capability

DEFF Research Database (Denmark)

Gajanayake, C.J.; Vilathgamuwa, D.M.; Loh, P.C.

2007-01-01

Distributed generation has been gaining acceptance over the years and it has the potential to provide reliable power to sensitive loads. However, distributed networks are prone to unbalanced faults conditions. This makes single inverter DG systems unsuitable as UPS systems. This paper proposes...... a Zsource inverter based power quality compensator and a control structure that supplies high quality voltage to the connected sensitive load in the presence of other non linear loads. The proposed topology consists of combination of shunt and series inverters connected to a common Z-source impedance...... network. The shunt inverter is controlled to maintain a quality voltage waveform at the load bus. Whereas the series inverter enhances the ride-through capability during grid faults, protects the shunt inverter by limiting the current and also controls the power delivered to the grid. The performance...

Topography-Dependent Motion Compensation: Application to UAVSAR Data

Science.gov (United States)

Jones, Cathleen E.; Hensley, Scott; Michel, Thierry

2009-01-01

The UAVSAR L-band synthetic aperture radar system has been designed for repeat track interferometry in support of Earth science applications that require high-precision measurements of small surface deformations over timescales from hours to years. Conventional motion compensation algorithms, which are based upon assumptions of a narrow beam and flat terrain, yield unacceptably large errors in areas with even moderate topographic relief, i.e., in most areas of interest. This often limits the ability to achieve sub-centimeter surface change detection over significant portions of an acquired scene. To reduce this source of error in the interferometric phase, we have implemented an advanced motion compensation algorithm that corrects for the scene topography and radar beam width. Here we discuss the algorithm used, its implementation in the UAVSAR data processor, and the improvement in interferometric phase and correlation achieved in areas with significant topographic relief.

A study on multi-point gravity compensation of mirror bending system

International Nuclear Information System (INIS)

Sun Fuquan; Fu Yuan; Zhu Wanqian; Xue Song

2011-01-01

The sag of mirror due to gravity induces unacceptable slope errors in beamline mirror-bending system of a synchrotron radiation facility, and approaches must be found to eliminate the unwanted gravity effect. According to the beam bending theory, the multi-point gravity compensation method is applicable. Taking an example of the bent collimating mirror for the XAFS beam-line (BL14W) at Shanghai Synchrotron Radiation Facility (SSRF), the best position and value of the equilibrant were calculated through minimizing the gravity effect. With two, three and four points gravity compensation, slope errors were 0.179, 0.067 and 0.032 μrad,respectively, i.e.the multi-point gravity compensation is better than the two-point gravity compensation, which is used for the Phase I beamlines of SSRF. The four-point gravity compensation method reduces more slope error and stress due to four support points. (authors)

Compensability index for compensation radiotherapy after treatment interruptions

International Nuclear Information System (INIS)

Putora, Paul Martin; Schmuecking, Michael; Aebersold, Daniel; Plasswilm, Ludwig

2012-01-01

The goal of our work was to develop a simple method to evaluate a compensation treatment after unplanned treatment interruptions with respect to their tumour- and normal tissue effect. We developed a software tool in java programming language based on existing recommendations to compensate for treatment interruptions. In order to express and visualize the deviations from the originally planned tumour and normal tissue effects we defined the compensability index. The compensability index represents an evaluation of the suitability of compensatory radiotherapy in a single number based on the number of days used for compensation and the preference of preserving the originally planned tumour effect or not exceeding the originally planned normal tissue effect. An automated tool provides a method for quick evaluation of compensation treatments. The compensability index calculation may serve as a decision support system based on existing and established recommendations

Sliding Mode Control for NSVs with Input Constraint Using Neural Network and Disturbance Observer

Directory of Open Access Journals (Sweden)

Yan-long Zhou

2013-01-01

Full Text Available The sliding mode control (SMC scheme is proposed for near space vehicles (NSVs with strong nonlinearity, high coupling, parameter uncertainty, and unknown time-varying disturbance based on radial basis function neural networks (RBFNNs and the nonlinear disturbance observer (NDO. Considering saturation characteristic of rudders, RBFNNs are constructed as a compensator to overcome the saturation nonlinearity. The stability of the closed-loop system is proved, and the tracking error as well as the disturbance observer error can converge to the origin through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed flight control scheme.

Non-binary coded modulation for FMF-based coherent optical transport networks

Science.gov (United States)

Lin, Changyu

The Internet has fundamentally changed the way of modern communication. Current trends indicate that high-capacity demands are not going to be saturated anytime soon. From Shannon's theory, we know that information capacity is a logarithmic function of signal-to-noise ratio (SNR), but a linear function of the number of dimensions. Ideally, we can increase the capacity by increasing the launch power, however, due to the nonlinear characteristics of silica optical fibers that imposes a constraint on the maximum achievable optical-signal-to-noise ratio (OSNR). So there exists a nonlinear capacity limit on the standard single mode fiber (SSMF). In order to satisfy never ending capacity demands, there are several attempts to employ additional degrees of freedom in transmission system, such as few-mode fibers (FMFs), which can dramatically improve the spectral efficiency. On the other hand, for the given physical links and network equipment, an effective solution to relax the OSNR requirement is based on forward error correction (FEC), as the response to the demands of high speed reliable transmission. In this dissertation, we first discuss the model of FMF with nonlinear effects considered. Secondly, we simulate the FMF based OFDM system with various compensation and modulation schemes. Thirdly, we propose tandem-turbo-product nonbinary byte-interleaved coded modulation (BICM) for next-generation high-speed optical transmission systems. Fourthly, we study the Q factor and mutual information as threshold in BICM scheme. Lastly, an experimental study of the limits of nonlinearity compensation with digital signal processing has been conducted.

Essays on executive equity-based compensation and equity ownership

OpenAIRE

Elsilä, A. (Anna)

2015-01-01

Abstract A major proposition of the agency theory is that the conflict of interests between an agent and a principal is reduced when the agent’s wealth and compensation are tied to the performance of the firm. Apart from the direct predicted relation to corporate performance, compensating managers with equity instruments has implications for corporate risk-taking and payout policy choices. Additionally, equity-based compensation practices are to a large extent shaped by institutional facto...

Human errors and violations in computer and information security: the viewpoint of network administrators and security specialists.

Science.gov (United States)

Kraemer, Sara; Carayon, Pascale

2007-03-01

This paper describes human errors and violations of end users and network administration in computer and information security. This information is summarized in a conceptual framework for examining the human and organizational factors contributing to computer and information security. This framework includes human error taxonomies to describe the work conditions that contribute adversely to computer and information security, i.e. to security vulnerabilities and breaches. The issue of human error and violation in computer and information security was explored through a series of 16 interviews with network administrators and security specialists. The interviews were audio taped, transcribed, and analyzed by coding specific themes in a node structure. The result is an expanded framework that classifies types of human error and identifies specific human and organizational factors that contribute to computer and information security. Network administrators tended to view errors created by end users as more intentional than unintentional, while errors created by network administrators as more unintentional than intentional. Organizational factors, such as communication, security culture, policy, and organizational structure, were the most frequently cited factors associated with computer and information security.

Die Face Engineering based Springback Compensation Strategy and Implementation

International Nuclear Information System (INIS)

Tang, Arthur; Lee Wing; He, Jeanne; Xu Jinbo; Liu Kesu; Chen Chinchun

2005-01-01

Springback or shape change has been one of the major challenges in sheet metal fabrication, particularly with increase application of high strength steel (HSS) and aluminum alloys in automotive stamping. Springback, an elastic material recovery after the unloading of stamping tools, causes variations and inconsistencies of final part dimensions. Minor or mild springback usually can be corrected in the re-strike process. Excessive springback must be corrected so the part will be produced within the given design tolerance and dimension. The commonly used Spring Forward approaches and shape compensations such as over-crown and over-bending are proven effective to alleviate excessive springback. To enhance these approaches, a new strategy of Die Face Engineering (DFE) based processing is proposed to quickly and easily to achieve the maximum allowable compensation using the under cut (or die lock) as the primary criteria. The implementation of the die face compensation through iterative FEA calculation, automatic surface mapping, projection and manual morphing are crucial to meet production environment requirements in terms of generating NC quality CAD surfaces of the compensated or morphed die face. In this paper, the strategy of the die face compensation with the consideration of the under cut criteria is presented. The implementation of various processes to enable user to perform the die face compensation task in a production environment is also discussed. Finally, two examples are shown to demonstrate the implementation of the proposed springback compensation scheme based on the combined CAE/CAD methodology

Controlling qubit drift by recycling error correction syndromes

Science.gov (United States)

Blume-Kohout, Robin

2015-03-01

Physical qubits are susceptible to systematic drift, above and beyond the stochastic Markovian noise that motivates quantum error correction. This parameter drift must be compensated - if it is ignored, error rates will rise to intolerable levels - but compensation requires knowing the parameters' current value, which appears to require halting experimental work to recalibrate (e.g. via quantum tomography). Fortunately, this is untrue. I show how to perform on-the-fly recalibration on the physical qubits in an error correcting code, using only information from the error correction syndromes. The algorithm for detecting and compensating drift is very simple - yet, remarkably, when used to compensate Brownian drift in the qubit Hamiltonian, it achieves a stabilized error rate very close to the theoretical lower bound. Against 1/f noise, it is less effective only because 1/f noise is (like white noise) dominated by high-frequency fluctuations that are uncompensatable. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE

Compensability index for compensation radiotherapy after treatment interruptions

Directory of Open Access Journals (Sweden)

Putora Paul

2012-12-01

Full Text Available Abstract Background The goal of our work was to develop a simple method to evaluate a compensation treatment after unplanned treatment interruptions with respect to their tumour- and normal tissue effect. Methods We developed a software tool in java programming language based on existing recommendations to compensate for treatment interruptions. In order to express and visualize the deviations from the originally planned tumour and normal tissue effects we defined the compensability index. Results The compensability index represents an evaluation of the suitability of compensatory radiotherapy in a single number based on the number of days used for compensation and the preference of preserving the originally planned tumour effect or not exceeding the originally planned normal tissue effect. An automated tool provides a method for quick evaluation of compensation treatments. Conclusions The compensability index calculation may serve as a decision support system based on existing and established recommendations.

A self-adaption compensation control for hysteresis nonlinearity in piezo-actuated stages based on Pi-sigma fuzzy neural network

Science.gov (United States)

Xu, Rui; Zhou, Miaolei

2018-04-01

Piezo-actuated stages are widely applied in the high-precision positioning field nowadays. However, the inherent hysteresis nonlinearity in piezo-actuated stages greatly deteriorates the positioning accuracy of piezo-actuated stages. This paper first utilizes a nonlinear autoregressive moving average with exogenous inputs (NARMAX) model based on the Pi-sigma fuzzy neural network (PSFNN) to construct an online rate-dependent hysteresis model for describing the hysteresis nonlinearity in piezo-actuated stages. In order to improve the convergence rate of PSFNN and modeling precision, we adopt the gradient descent algorithm featuring three different learning factors to update the model parameters. The convergence of the NARMAX model based on the PSFNN is analyzed effectively. To ensure that the parameters can converge to the true values, the persistent excitation condition is considered. Then, a self-adaption compensation controller is designed for eliminating the hysteresis nonlinearity in piezo-actuated stages. A merit of the proposed controller is that it can directly eliminate the complex hysteresis nonlinearity in piezo-actuated stages without any inverse dynamic models. To demonstrate the effectiveness of the proposed model and control methods, a set of comparative experiments are performed on piezo-actuated stages. Experimental results show that the proposed modeling and control methods have excellent performance.

Adaptive compensation control for attitude adjustment of quad-rotor unmanned aerial vehicle.

Science.gov (United States)

Song, Zhankui; Sun, Kaibiao

2017-07-01

A compensation control strategy based on adaptive back-stepping technique is presented to address the problem of attitude adjustment for a quad-rotor unmanned aerial vehicle (QR- UAV) with inertia parameter uncertainties, the limited airflow disturbance and the partial loss of rotation speed effectiveness. In the design process of control system, adaptive estimation technique is introduced into the closed loop system in order to compensate the lumped disturbance term. More specifically, the designed controller utilizes "prescribed performance bounds" method, and therefore guarantees the transient performance of tracking errors, even in the presence of the lumped disturbance. Adaptive compensation algorithms under the proposed closed loop system structure are derived in the sense of Lyapunov stability analysis such that the attitude tracking error converge to a small neighborhood of equilibrium point. Finally, the simulation results demonstrate the effectiveness of the proposed controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Router Agent Technology for Policy-Based Network Management

Science.gov (United States)

Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

2011-01-01

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

Error analysis and algorithm implementation for an improved optical-electric tracking device based on MEMS

Science.gov (United States)

Sun, Hong; Wu, Qian-zhong

2013-09-01

In order to improve the precision of optical-electric tracking device, proposing a kind of improved optical-electric tracking device based on MEMS, in allusion to the tracking error of gyroscope senor and the random drift, According to the principles of time series analysis of random sequence, establish AR model of gyro random error based on Kalman filter algorithm, then the output signals of gyro are multiple filtered with Kalman filter. And use ARM as micro controller servo motor is controlled by fuzzy PID full closed loop control algorithm, and add advanced correction and feed-forward links to improve response lag of angle input, Free-forward can make output perfectly follow input. The function of lead compensation link is to shorten the response of input signals, so as to reduce errors. Use the wireless video monitor module and remote monitoring software (Visual Basic 6.0) to monitor servo motor state in real time, the video monitor module gathers video signals, and the wireless video module will sent these signals to upper computer, so that show the motor running state in the window of Visual Basic 6.0. At the same time, take a detailed analysis to the main error source. Through the quantitative analysis of the errors from bandwidth and gyro sensor, it makes the proportion of each error in the whole error more intuitive, consequently, decrease the error of the system. Through the simulation and experiment results shows the system has good following characteristic, and it is very valuable for engineering application.

Compensation of significant parametric uncertainties using sliding mode online learning

Science.gov (United States)

Schnetter, Philipp; Kruger, Thomas

An augmented nonlinear inverse dynamics (NID) flight control strategy using sliding mode online learning for a small unmanned aircraft system (UAS) is presented. Because parameter identification for this class of aircraft often is not valid throughout the complete flight envelope, aerodynamic parameters used for model based control strategies may show significant deviations. For the concept of feedback linearization this leads to inversion errors that in combination with the distinctive susceptibility of small UAS towards atmospheric turbulence pose a demanding control task for these systems. In this work an adaptive flight control strategy using feedforward neural networks for counteracting such nonlinear effects is augmented with the concept of sliding mode control (SMC). SMC-learning is derived from variable structure theory. It considers a neural network and its training as a control problem. It is shown that by the dynamic calculation of the learning rates, stability can be guaranteed and thus increase the robustness against external disturbances and system failures. With the resulting higher speed of convergence a wide range of simultaneously occurring disturbances can be compensated. The SMC-based flight controller is tested and compared to the standard gradient descent (GD) backpropagation algorithm under the influence of significant model uncertainties and system failures.

Analysis and Compensation for Lateral Chromatic Aberration in a Color Coding Structured Light 3D Measurement System

Science.gov (United States)

Huang, Junhui; Xue, Qi; Wang, Zhao; Gao, Jianmin

2016-01-01

While color-coding methods have improved the measuring efficiency of a structured light three-dimensional (3D) measurement system, they decreased the measuring accuracy significantly due to lateral chromatic aberration (LCA). In this study, the LCA in a structured light measurement system is analyzed, and a method is proposed to compensate the error caused by the LCA. Firstly, based on the projective transformation, a 3D error map of LCA is constructed in the projector images by using a flat board and comparing the image coordinates of red, green and blue circles with the coordinates of white circles at preselected sample points within the measurement volume. The 3D map consists of the errors, which are the equivalent errors caused by LCA of the camera and projector. Then in measurements, error values of LCA are calculated and compensated to correct the projector image coordinates through the 3D error map and a tri-linear interpolation method. Eventually, 3D coordinates with higher accuracy are re-calculated according to the compensated image coordinates. The effectiveness of the proposed method is verified in the following experiments. PMID:27598174

Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics

Directory of Open Access Journals (Sweden)

Carlos González-Gutiérrez

2018-01-01

Full Text Available Aberrations introduced by the atmospheric turbulence in large telescopes are compensated using adaptive optics systems, where the use of deformable mirrors and multiple sensors relies on complex control systems. Recently, the development of larger scales of telescopes as the E-ELT or TMT has created a computational challenge due to the increasing complexity of the new adaptive optics systems. The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. During recent years, the use of GPUs has been proved to be a great solution to speed up the learning process of neural networks, and different frameworks have been created to ease their development. The implementation of CARMEN in different Multi-GPU frameworks is presented in this paper, along with its development in a language originally developed for GPU, like CUDA. This implementation offers the best response for all the presented cases, although its advantage of using more than one GPU occurs only in large networks.

Error and attack tolerance of synchronization in Hindmarsh–Rose neural networks with community structure

International Nuclear Information System (INIS)

Li, Chun-Hsien; Yang, Suh-Yuh

2014-01-01

Synchronization is one of the most important features observed in large-scale complex networks of interacting dynamical systems. As is well known, there is a close relation between the network topology and the network synchronizability. Using the coupled Hindmarsh–Rose neurons with community structure as a model network, in this paper we explore how failures of the nodes due to random errors or intentional attacks affect the synchronizability of community networks. The intentional attacks are realized by removing a fraction of the nodes with high values in some centrality measure such as the centralities of degree, eigenvector, betweenness and closeness. According to the master stability function method, we employ the algebraic connectivity of the considered community network as an indicator to examine the network synchronizability. Numerical evidences show that the node failure strategy based on the betweenness centrality has the most influence on the synchronizability of community networks. With this node failure strategy for a given network with a fixed number of communities, we find that the larger the degree of communities, the worse the network synchronizability; however, for a given network with a fixed degree of communities, we observe that the more the number of communities, the better the network synchronizability.

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

Science.gov (United States)

Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George

2017-06-26

We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.

Fault detection for hydraulic pump based on chaotic parallel RBF network

Directory of Open Access Journals (Sweden)

Ma Ning

2011-01-01

Full Text Available Abstract In this article, a parallel radial basis function network in conjunction with chaos theory (CPRBF network is presented, and applied to practical fault detection for hydraulic pump, which is a critical component in aircraft. The CPRBF network consists of a number of radial basis function (RBF subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of CPRBF is a weighted sum of all RBF subnets. It was first trained using the dataset from normal state without fault, and then a residual error generator was designed to detect failures based on the trained CPRBF network. Then, failure detection can be achieved by the analysis of the residual error. Finally, two case studies are introduced to compare the proposed CPRBF network with traditional RBF networks, in terms of prediction and detection accuracy.

Stochastic Wheel-Slip Compensation Based Robot Localization and Mapping

Directory of Open Access Journals (Sweden)

SIDHARTHAN, R. K.

2016-05-01

Full Text Available Wheel slip compensation is vital for building accurate and reliable dead reckoning based robot localization and mapping algorithms. This investigation presents stochastic slip compensation scheme for robot localization and mapping. Main idea of the slip compensation technique is to use wheel-slip data obtained from experiments to model the variations in slip velocity as Gaussian distributions. This leads to a family of models that are switched depending on the input command. To obtain the wheel-slip measurements, experiments are conducted on a wheeled mobile robot and the measurements thus obtained are used to build the Gaussian models. Then the localization and mapping algorithm is tested on an experimental terrain and a new metric called the map spread factor is used to evaluate the ability of the slip compensation technique. Our results clearly indicate that the proposed methodology improves the accuracy by 72.55% for rotation and 66.67% for translation motion as against an uncompensated mapping system. The proposed compensation technique eliminates the need for extro receptive sensors for slip compensation, complex feature extraction and association algorithms. As a result, we obtain a simple slip compensation scheme for localization and mapping.

Research on High-Precision, Low Cost Piezoresistive MEMS-Array Pressure Transmitters Based on Genetic Wavelet Neural Networks for Meteorological Measurements

Directory of Open Access Journals (Sweden)

Jiahong Zhang

2015-05-01

Full Text Available This paper provides a novel and effective compensation method by improving the hardware design and software algorithm to achieve optimization of piezoresistive pressure sensors and corresponding measurement systems in order to measure pressure more accurately and stably, as well as to meet the application requirements of the meteorological industry. Specifically, GE NovaSensor MEMS piezoresistive pressure sensors within a thousandth of accuracy are selected to constitute an array. In the versatile compensation method, the hardware utilizes the array of MEMS pressure sensors to reduce random error caused by sensor creep, and the software adopts the data fusion technique based on the wavelet neural network (WNN which is improved by genetic algorithm (GA to analyze the data of sensors for the sake of obtaining accurate and complete information over the wide temperature and pressure ranges. The GA-WNN model is implemented in hardware by using the 32-bit STMicroelectronics (STM32 microcontroller combined with an embedded real-time operating system µC/OS-II to make the output of the array of MEMS sensors be a direct digital readout. The results of calibration and test experiments clearly show that the GA-WNN technique can be effectively applied to minimize the sensor errors due to the temperature drift, the hysteresis effect and the long-term drift because of aging and environmental changes. The maximum error of the low cost piezoresistive MEMS-array pressure transmitter proposed by us is within 0.04% of its full-scale value, and it can satisfy the meteorological pressure measurement.

An improved current control scheme for grid-connected DG unit based distribution system harmonic compensation

DEFF Research Database (Denmark)

He, Jinwei; Wei Li, Yun; Wang, Xiongfei

2013-01-01

In order to utilize DG unit interfacing converters to actively compensate distribution system harmonics, this paper proposes an enhanced current control approach. It seamlessly integrates system harmonic mitigation capabilities with the primary DG power generation function. As the proposed current...... controller has two well decoupled control branches to independently control fundamental and harmonic DG currents, phase-locked loops (PLL) and system harmonic component extractions can be avoided during system harmonic compensation. Moreover, a closed-loop power control scheme is also employed to derive...... the fundamental current reference. The proposed power control scheme effectively eliminates the impacts of steady-state fundamental current tracking errors in the DG units. Thus, an accurate power control is realized even when the harmonic compensation functions are activated. Experimental results from a single...

48 CFR 52.228-3 - Workers' Compensation Insurance (Defense Base Act).

Science.gov (United States)

2010-10-01

... Insurance (Defense Base Act). 52.228-3 Section 52.228-3 Federal Acquisition Regulations System FEDERAL... Provisions and Clauses 52.228-3 Workers' Compensation Insurance (Defense Base Act). As prescribed in 28.309(a), insert the following clause: Workers' Compensation Insurance (Defense Base Act) (APR 1984) The Contractor...

An Enhanced Intelligent Handheld Instrument with Visual Servo Control for 2-DOF Hand Motion Error Compensation

Directory of Open Access Journals (Sweden)

Yan Naing Aye

2013-10-01

Full Text Available The intelligent handheld instrument, ITrem2, enhances manual positioning accuracy by cancelling erroneous hand movements and, at the same time, provides automatic micromanipulation functions. Visual data is acquired from a high speed monovision camera attached to the optical surgical microscope and acceleration measurements are acquired from the inertial measurement unit (IMU on board ITrem2. Tremor estimation and canceling is implemented via Band-limited Multiple Fourier Linear Combiner (BMFLC filter. The piezoelectric actuated micromanipulator in ITrem2 generates the 3D motion to compensate erroneous hand motion. Preliminary bench-top 2-DOF experiments have been conducted. The error motions simulated by a motion stage is reduced by 67% for multiple frequency oscillatory motions and 56.16% for pre-conditioned recorded physiological tremor.

Large-scale compensation of errors in pairwise-additive empirical force fields: comparison of AMBER intermolecular terms with rigorous DFT-SAPT calculations

Czech Academy of Sciences Publication Activity Database

Zgarbová, M.; Otyepka, M.; Šponer, Jiří; Hobza, P.; Jurečka, P.

2010-01-01

Roč. 12, č. 35 (2010), s. 10476-10493 ISSN 1463-9076 R&D Projects: GA ČR(CZ) GA203/09/1476 Grant - others:GA MŠk(CZ) LC512; GA MŠk(CZ) GD203/09/H046 Program:LC; GD Institutional research plan: CEZ:AV0Z50040507; CEZ:AV0Z50040702 Keywords : amber empirical potential * DFT-SAPT * compensation of errors Subject RIV: BO - Biophysics Impact factor: 3.454, year: 2010

A GA-based PID active queue management control design for TCP/IP networks

Energy Technology Data Exchange (ETDEWEB)

Kuo, H-H; Chen, C-K; Liao, T-L [Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan (China); Yan, J-J [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: tlliao@mail.ncku.edu.tw

2008-02-15

In this paper, a genetic algorithm-based (GA-based) proportional-integral-derivative (PID) controller as an active queue manager for Internet routers is proposed to reduce packet loss and improve network utilization in TCP/IP networks. Based on the window-based nonlinear dynamics, the TCP network was modeled as a time-delayed system with a saturated input due to the limitations of packet-dropping probability and the effects of propagation delays in TCP networks. An improved genetic algorithm is employed to derive optimal or near optimal PID control gains such that a performance index of integrated-absolute error (IAE) in terms of the error between the router queue length and the desired queue length is minimized. The performance of the proposed control scheme was evaluated in various network scenarios via a series of numerical simulations. The simulation results confirm that the proposed scheme outperforms other AQM schemes.

A GA-based PID active queue management control design for TCP/IP networks

International Nuclear Information System (INIS)

Kuo, H-H; Chen, C-K; Liao, T-L; Yan, J-J

2008-01-01

In this paper, a genetic algorithm-based (GA-based) proportional-integral-derivative (PID) controller as an active queue manager for Internet routers is proposed to reduce packet loss and improve network utilization in TCP/IP networks. Based on the window-based nonlinear dynamics, the TCP network was modeled as a time-delayed system with a saturated input due to the limitations of packet-dropping probability and the effects of propagation delays in TCP networks. An improved genetic algorithm is employed to derive optimal or near optimal PID control gains such that a performance index of integrated-absolute error (IAE) in terms of the error between the router queue length and the desired queue length is minimized. The performance of the proposed control scheme was evaluated in various network scenarios via a series of numerical simulations. The simulation results confirm that the proposed scheme outperforms other AQM schemes

The voice of conscience: neural bases of interpersonal guilt and compensation

Science.gov (United States)

Yu, Hongbo; Hu, Jie; Hu, Li

2014-01-01

People feel bad for inflicting harms upon others; this emotional state is termed interpersonal guilt. In this study, the participant played multiple rounds of a dot-estimation task with anonymous partners while undergoing fMRI. The partner would receive pain stimulation if the partner or the participant or both responded incorrectly; the participant was then given the option to intervene and bear a proportion of pain for the partner. The level of pain voluntarily taken and the activations in anterior middle cingulate cortex (aMCC) and bilateral anterior insula (AI) were higher when the participant was solely responsible for the stimulation (Self_Incorrect) than when both committed an error (Both_Incorrect). Moreover, the gray matter volume in the aMCC predicted the individual’s compensation behavior, measured as the difference between the level of pain taken in the Self_Incorrect and Both_Incorrect conditions. Furthermore, a mediation pathway analysis revealed that activation in a midbrain region mediated the relationship between aMCC activation and the individual’s tendency to compensate. These results demonstrate that the aMCC and the midbrain nucleus not only play an important role in experiencing interpersonal guilt, but also contribute to compensation behavior. PMID:23893848

Hysteresis Compensation and Sliding Mode Control with Perturbation Estimation for Piezoelectric Actuators

Directory of Open Access Journals (Sweden)

Bingxiao Ding

2018-05-01

Full Text Available Based on the background of atomic force microscope (AFM driven by piezoelectric actuators (PEAs, this paper proposes a sliding mode control coupled with an inverse Bouc–Wen (BW hysteresis compensator to improve the positioning performance of PEAs. The intrinsic hysteresis and creep characteristics degrade the performance of the PEA and cause accuracy loss. Although creep effect can be eliminated by the closed-loop control approach, hysteresis effects need to be compensated and alleviated by hysteresis compensators. For the purpose of dealing with the estimation errors, unmodeled vibration, and disturbances, a sliding mode control with perturbation estimation (SMCPE method is adopted to enhance the performance and robustness of the system. In order to validate the feasibility and performance of the proposed method, experimental studies are carried out, and the results show that the proposed controller performs better than a proportional-integral-derivative (PID controller at 1 and 2 Hz, reducing error to 1.2% and 1.4%, respectively.

Topological quantum computing with a very noisy network and local error rates approaching one percent.

Science.gov (United States)

Nickerson, Naomi H; Li, Ying; Benjamin, Simon C

2013-01-01

A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.

Numeral eddy current sensor modelling based on genetic neural network

International Nuclear Information System (INIS)

Yu Along

2008-01-01

This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method

A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation

Directory of Open Access Journals (Sweden)

Tianshuang Qiu

2007-12-01

Full Text Available This paper proposes a geometric method to locate a mobile station (MS in a mobile cellular network when both the range and angle measurements are corrupted by non-line-of-sight (NLOS errors. The MS location is restricted to an enclosed region by geometric constraints from the temporal-spatial characteristics of the radio propagation channel. A closed-form equation of the MS position, time of arrival (TOA, angle of arrival (AOA, and angle spread is provided. The solution space of the equation is very large because the angle spreads are random variables in nature. A constrained objective function is constructed to further limit the MS position. A Lagrange multiplier-based solution and a numerical solution are proposed to resolve the MS position. The estimation quality of the estimator in term of “biased” or “unbiased” is discussed. The scale factors, which may be used to evaluate NLOS propagation level, can be estimated by the proposed method. AOA seen at base stations may be corrected to some degree. The performance comparisons among the proposed method and other hybrid location methods are investigated on different NLOS error models and with two scenarios of cell layout. It is found that the proposed method can deal with NLOS error effectively, and it is attractive for location estimation in cellular networks.

Supervisory Adaptive Network-Based Fuzzy Inference System (SANFIS Design for Empirical Test of Mobile Robot

Directory of Open Access Journals (Sweden)

Yi-Jen Mon

2012-10-01

Full Text Available A supervisory Adaptive Network-based Fuzzy Inference System (SANFIS is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off-line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error between the ANFIS controller and the ideal controller, and drive the trajectory of the system onto a specified surface (called the sliding surface or switching surface while maintaining the trajectory onto this switching surface continuously to guarantee the system stability. This SANFIS controller can achieve favourable empirical control performance of the mobile robot in the empirical tests of driving the mobile robot with a square path. Practical experimental results demonstrate that the proposed SANFIS can achieve better control performance than that achieved using an ANFIS controller for empirical control of the mobile robot.

Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

Directory of Open Access Journals (Sweden)

Zhonghua Wu

2017-02-01

Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

A Combined Gravity Compensation Method for INS Using the Simplified Gravity Model and Gravity Database.

Science.gov (United States)

Zhou, Xiao; Yang, Gongliu; Wang, Jing; Wen, Zeyang

2018-05-14

In recent decades, gravity compensation has become an important way to reduce the position error of an inertial navigation system (INS), especially for a high-precision INS, because of the extensive application of high precision inertial sensors (accelerometers and gyros). This paper first deducts the INS's solution error considering gravity disturbance and simulates the results. Meanwhile, this paper proposes a combined gravity compensation method using a simplified gravity model and gravity database. This new combined method consists of two steps all together. Step 1 subtracts the normal gravity using a simplified gravity model. Step 2 first obtains the gravity disturbance on the trajectory of the carrier with the help of ELM training based on the measured gravity data (provided by Institute of Geodesy and Geophysics; Chinese Academy of sciences), and then compensates it into the error equations of the INS, considering the gravity disturbance, to further improve the navigation accuracy. The effectiveness and feasibility of this new gravity compensation method for the INS are verified through vehicle tests in two different regions; one is in flat terrain with mild gravity variation and the other is in complex terrain with fierce gravity variation. During 2 h vehicle tests, the positioning accuracy of two tests can improve by 20% and 38% respectively, after the gravity is compensated by the proposed method.

Study on Compensation Control of STATCOM Based on MMC

Directory of Open Access Journals (Sweden)

Xie Yan

2016-01-01

Full Text Available This paper introduced modular multi-level converter (MMC, which could enhance the voltage and power level by sub-converter modules in series and was easy to extend to any level of output. Its structure and working mechanism were described. By analyzing the energy transfer performance of STATCOM based on MMC working conditions in the compensation, a comprehensive compensation control strategy was proposed based on direct current control mode. By analyzing the higher harmonic components circulation generated by the inconsistencies in the three-phase upper and lower arm voltage, a loop control strategy is proposed for the suppression of the circulation in the arms of the M-STATCOM. The simulation results show the strategy has a better tracking precision and response speed for the compensation control.

Semiparametric modeling: Correcting low-dimensional model error in parametric models

International Nuclear Information System (INIS)

Berry, Tyrus; Harlim, John

2016-01-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.

Calibration and Distortion Field Compensation of Gradiometer and the Improvement in Object Remote Sensing

Directory of Open Access Journals (Sweden)

Hu Xiangchao

2016-01-01

Full Text Available Magnetometer, misalignment error and distortion field can reduce the accuracy of gradiometers. So, it is important to calibrate and compensate gradiometers error. Scale factor, bias, nonorthogonality, misalignment and distortion field should be considered. A gradiometer is connected by an aluminium frame, which contains two fluxgate magnetometers. A nonmagnetic rotation equipment is used to change gradiometer attitude, and the compensation parameters are estimated. Experiment results show that, after calibration and compensation, error of each axis is reduced from 888.4 nT, 1292.6 nT and 168.9 nT to 15.3 nT, 22.1 nT and 9.9 nT, respectively. It shows that the proposed method can calibrate gradiometer and compensate distortion field. After calibration and compensation, the object remote sensing performance is improved.

Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

Science.gov (United States)

Ho, Ching S.; Liou, Juin J.; Georgiopoulos, Michael; Christodoulou, Christos G.

1994-03-01

This paper presents an analog circuit design and implementation for an adaptive resonance theory neural network architecture called the augmented ART1 neural network (AART1-NN). Practical monolithic operational amplifiers (Op-Amps) LM741 and LM318 are selected to implement the circuit, and a simple compensation scheme is developed to adjust the Op-Amp electrical characteristics to meet the design requirement. A 7-node prototype circuit has been designed and verified using the Pspice circuit simulator run on a Sun workstation. Results simulated from the AART1-NN circuit using the LM741, LM318, and ideal Op-Amps are presented and compared.

Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems

Directory of Open Access Journals (Sweden)

Ruonan Wu

2016-12-01

Full Text Available The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV. Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008, namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs.

Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems.

Science.gov (United States)

Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Liu, Tianyi; Hu, Peida; Li, Haixia

2016-12-18

The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs) with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV). Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008), namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs.

Robustness of a Neural Network Model for Power Peak Factor Estimation in Protection Systems

International Nuclear Information System (INIS)

Souza, Rose Mary G.P.; Moreira, Joao M.L.

2006-01-01

This work presents results of robustness verification of artificial neural network correlations that improve the real time prediction of the power peak factor for reactor protection systems. The input variables considered in the correlation are those available in the reactor protection systems, namely, the axial power differences obtained from measured ex-core detectors, and the position of control rods. The correlations, based on radial basis function (RBF) and multilayer perceptron (MLP) neural networks, estimate the power peak factor, without faulty signals, with average errors between 0.13%, 0.19% and 0.15%, and maximum relative error of 2.35%. The robustness verification was performed for three different neural network correlations. The results show that they are robust against signal degradation, producing results with faulty signals with a maximum error of 6.90%. The average error associated to faulty signals for the MLP network is about half of that of the RBF network, and the maximum error is about 1% smaller. These results demonstrate that MLP neural network correlation is more robust than the RBF neural network correlation. The results also show that the input variables present redundant information. The axial power difference signals compensate the faulty signal for the position of a given control rod, and improves the results by about 10%. The results show that the errors in the power peak factor estimation by these neural network correlations, even in faulty conditions, are smaller than the current PWR schemes which may have uncertainties as high as 8%. Considering the maximum relative error of 2.35%, these neural network correlations would allow decreasing the power peak factor safety margin by about 5%. Such a reduction could be used for operating the reactor with a higher power level or with more flexibility. The neural network correlation has to meet requirements of high integrity software that performs safety grade actions. It is shown that the

The design of multi-lead-compensators for stabilization and pole placement in double-integrator networks under saturation

NARCIS (Netherlands)

Wan, Yan; Roy, Sandip; Saberi, Ali; Stoorvogel, Antonie Arij

2009-01-01

We study decentralized controller design for stabilization and pole-placement, in a network of autonomous agents with double-integrator internal dynamics and arbitrary observation topology. We show that a simple multi-lead-compensator architecture, in particular one in which each agent uses a

Financial impact of errors in business forecasting: a comparative study of linear models and neural networks

Directory of Open Access Journals (Sweden)

Claudimar Pereira da Veiga

2012-08-01

Full Text Available The importance of demand forecasting as a management tool is a well documented issue. However, it is difficult to measure costs generated by forecasting errors and to find a model that assimilate the detailed operation of each company adequately. In general, when linear models fail in the forecasting process, more complex nonlinear models are considered. Although some studies comparing traditional models and neural networks have been conducted in the literature, the conclusions are usually contradictory. In this sense, the objective was to compare the accuracy of linear methods and neural networks with the current method used by the company. The results of this analysis also served as input to evaluate influence of errors in demand forecasting on the financial performance of the company. The study was based on historical data from five groups of food products, from 2004 to 2008. In general, one can affirm that all models tested presented good results (much better than the current forecasting method used, with mean absolute percent error (MAPE around 10%. The total financial impact for the company was 6,05% on annual sales.

Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach

KAUST Repository

Afify, Laila H.

2015-09-14

In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. The analysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goes beyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques to model the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoretical findings of the paper are verified via Monte Carlo simulations.

Design of a base station for MEMS CCR localization in an optical sensor network.

Science.gov (United States)

Park, Chan Gook; Jeon, Hyun Cheol; Kim, Hyoun Jin; Kim, Jae Yoon

2014-05-08

This paper introduces a design and implementation of a base station, capable of positioning sensor nodes using an optical scheme. The base station consists of a pulse laser module, optical detectors and beam splitter, which are mounted on a rotation-stage, and a Time to Digital Converter (TDC). The optical pulse signal transmitted to the sensor node with a Corner Cube Retro-reflector (CCR) is reflected to the base station, and the Time of Flight (ToF) data can be obtained from the two detectors. With the angle and flight time data, the position of the sensor node can be calculated. The performance of the system is evaluated by using a commercial CCR. The sensor nodes are placed at different angles from the base station and scanned using the laser. We analyze the node position error caused by the rotation and propose error compensation methods, namely the outlier sample exception and decreasing the confidence factor steadily using the recursive least square (RLS) methods. Based on the commercial CCR results, the MEMS CCR is also tested to demonstrate the compatibility between the base station and the proposed methods. The result shows that the localization performance of the system can be enhanced with the proposed compensation method using the MEMS CCR.

Design of a Base Station for MEMS CCR Localization in an Optical Sensor Network

Directory of Open Access Journals (Sweden)

Chan Gook Park

2014-05-01

Full Text Available This paper introduces a design and implementation of a base station, capable of positioning sensor nodes using an optical scheme. The base station consists of a pulse laser module, optical detectors and beam splitter, which are mounted on a rotation-stage, and a Time to Digital Converter (TDC. The optical pulse signal transmitted to the sensor node with a Corner Cube Retro-reflector (CCR is reflected to the base station, and the Time of Flight (ToF data can be obtained from the two detectors. With the angle and flight time data, the position of the sensor node can be calculated. The performance of the system is evaluated by using a commercial CCR. The sensor nodes are placed at different angles from the base station and scanned using the laser. We analyze the node position error caused by the rotation and propose error compensation methods, namely the outlier sample exception and decreasing the confidence factor steadily using the recursive least square (RLS methods. Based on the commercial CCR results, the MEMS CCR is also tested to demonstrate the compatibility between the base station and the proposed methods. The result shows that the localization performance of the system can be enhanced with the proposed compensation method using the MEMS CCR.

Extension to HiRLoc Algorithm for Localization Error Computation in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Swati Saxena

2013-09-01

Full Text Available Wireless sensor networks (WSNs have gained importance in recent years as this support a large spectrum of applications such as automotive, health, military, environmental, home and office. Various algorithms have been proposed for making this technology more adaptive the existing algorithms address issues such as safety, security, power consumption, lifetime and localization. This paper presents an extension to HiRLoc algorithm and highlights its benefits. Extended HiRLoc significantly reduce the average localization error by suggesting a new method directional antenna based scheme.

Regulation System for the 18 kV/90 Mvar Compensators

CERN Document Server

Burdet, G

2001-01-01

Two 18 kV/90 Mvar static compensators are involved to stabilise the voltage, filter the harmonics and compensate the reactive power generated by the power converters used to supply the SPS accelerator magnets. The in-house hardware and software used by the regulation systems, difficult to maintain and upgrade, shall be renovated. Industrial solution based on PLC will be implemented. This paper describes the future system and its integration to the Electrical Network Supervisor.

Comprehensive Anti-error Study on Power Grid Dispatching Based on Regional Regulation and Integration

Science.gov (United States)

Zhang, Yunju; Chen, Zhongyi; Guo, Ming; Lin, Shunsheng; Yan, Yinyang

2018-01-01

With the large capacity of the power system, the development trend of the large unit and the high voltage, the scheduling operation is becoming more frequent and complicated, and the probability of operation error increases. This paper aims at the problem of the lack of anti-error function, single scheduling function and low working efficiency for technical support system in regional regulation and integration, the integrated construction of the error prevention of the integrated architecture of the system of dispatching anti - error of dispatching anti - error of power network based on cloud computing has been proposed. Integrated system of error prevention of Energy Management System, EMS, and Operation Management System, OMS have been constructed either. The system architecture has good scalability and adaptability, which can improve the computational efficiency, reduce the cost of system operation and maintenance, enhance the ability of regional regulation and anti-error checking with broad development prospects.

A flow-based methodology for the calculation of TSO to TSO compensations for cross-border flows

International Nuclear Information System (INIS)

Glavitsch, H.; Andersson, G.; Lekane, Th.; Marien, A.; Mees, E.; Naef, U.

2004-01-01

In the context of the development of the European internal electricity market, several methods for the tarification of cross-border flows have been proposed. This paper presents a flow-based method for the calculation of TSO to TSO compensations for cross-border flows. The basic principle of this approach is the allocation of the costs of cross-border flows to the TSOs who are responsible for these flows. This method is cost reflective, non-transaction based and compatible with domestic tariffs. It can be applied when limited data are available. Each internal transmission network is then modelled as an aggregated node, called 'supernode', and the European network is synthesized by a graph of supernodes and arcs, each arc representing all cross-border lines between two adjacent countries. When detailed data are available, the proposed methodology is also applicable to all the nodes and lines of the transmission network. Costs associated with flows transiting through supernodes or network elements are forwarded through the network in a way reflecting how the flows make use of the network. The costs can be charged either towards loads and exports or towards generations and imports. Combination of the two charging directions can also be considered. (author)

Urology Group Compensation and Ancillary Service Models in an Era of Value-based Care.

Science.gov (United States)

Shore, Neal D; Jacoby, Dana

2016-01-01

Changes involving the health care economic landscape have affected physicians' workflow, productivity, compensation structures, and culture. Ongoing Federal legislation regarding regulatory documentation and imminent payment-changing methodologies have encouraged physician consolidation into larger practices, creating affiliations with hospitals, multidisciplinary medical specialties, and integrated delivery networks. As subspecialization and evolution of care models have accelerated, independent medical groups have broadened ancillary service lines by investing in enterprises that compete with hospital-based (academic and nonacademic) entities, as well as non-physician- owned multispecialty enterprises, for both outpatient and inpatient services. The looming and dramatic shift from volume- to value-based health care compensation will assuredly affect urology group compensation arrangements and productivity formulae. For groups that can implement change rapidly, efficiently, and harmoniously, there will be opportunities to achieve the Triple Aim goals of the Patient Protection and Affordable Care Act, while maintaining a successful medical-financial practice. In summary, implementing new payment algorithms alongside comprehensive care coordination will assist urology groups in addressing the health economic cost and quality challenges that have been historically encountered with fee-for-service systems. Urology group leadership and stakeholders will need to adjust internal processes, methods of care coordination, cultural dependency, and organizational structures in order to create better systems of care and management. In response, ancillary services and patient throughput will need to evolve in order to adequately align quality measurement and reporting systems across provider footprints and patient populations.

Hysteresis compensation for piezoelectric actuators in single-point diamond turning

Science.gov (United States)

Wang, Haifeng; Hu, Dejin; Wan, Daping; Liu, Hongbin

2006-02-01

In recent years, interests have been growing for fast tool servo (FTS) systems to increase the capability of existing single-point diamond turning machines. Although piezoelectric actuator is the most universal base of FTS system due to its high stiffness, accuracy and bandwidth, nonlinearity in piezoceramics limits both the static and dynamic performance of piezoelectric-actuated control systems evidently. To compensate the nonlinear hysteresis behavior of piezoelectric actuators, a hybrid model coupled with Preisach model and feedforward neural network (FNN) has been described. Since the training of FNN does not require a special calibration sequence, it is possible for on-line identification and real-time implementation with general operating data of a specific piezoelectric actuator. To describe the rate dependent behavior of piezoelectric actuators, a hybrid dynamic model was developed to predict the response of piezoelectric actuators in a wider range of input frequency. Experimental results show that a maximal error of less than 3% was accomplished by this dynamic model.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

Science.gov (United States)

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander

2015-04-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. Copyright © 2015 the American Physiological Society.

Establishment of an eco-compensation fund based on eco-services consumption.

Science.gov (United States)

Liu, Moucheng; Yang, Lun; Min, Qingwen

2018-04-01

Eco-compensation is a type of institutional arrangement that uses economic measures to adjust the relationships among stakeholders in order to conserve and/or sustainably use ecosystem services. The externality of the value of ecosystem services is one of the theoretical bases for eco-compensation. Different types of ecosystem services are consumed by people from different regions. Some are consumed by people living where the services originate, while some are carried by rivers, wind, vehicles or other natural or manmade means to other areas. Thus, the flow and consumption of ecosystem services should be seen as the basis for establishing eco-compensation funds. This paper uses satellite images of the Zhang-Cheng area near Beijing in 2013 to discuss how to establish an eco-compensation fund for stakeholders in this area. Firstly, six important types of ecosystem services in the Zhang-Cheng area were identified based on ecological function zoning, and the value of these ecosystem services was calculated based on ecological pricing methods. Secondly, the field intensity model from physics was used to analyze where Zhang-Cheng area ecosystem services flowed and calculate how much of these services were used by other areas. Thirdly, based on this analysis and calculation, the paper proposes the rates that different stakeholders should invest in the eco-compensation fund, based on their consumption of eco-services. Copyright © 2018 Elsevier Ltd. All rights reserved.

DC-Compensated Current Transformer.

Science.gov (United States)

Ripka, Pavel; Draxler, Karel; Styblíková, Renata

2016-01-20

Instrument current transformers (CTs) measure AC currents. The DC component in the measured current can saturate the transformer and cause gross error. We use fluxgate detection and digital feedback compensation of the DC flux to suppress the overall error to 0.15%. This concept can be used not only for high-end CTs with a nanocrystalline core, but it also works for low-cost CTs with FeSi cores. The method described here allows simultaneous measurements of the DC current component.

Aerial robot intelligent control method based on back-stepping

Science.gov (United States)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors.

Science.gov (United States)

Khoshgoftaar, Taghi M; Van Hulse, Jason; Napolitano, Amri

2010-05-01

Neural network algorithms such as multilayer perceptrons (MLPs) and radial basis function networks (RBFNets) have been used to construct learners which exhibit strong predictive performance. Two data related issues that can have a detrimental impact on supervised learning initiatives are class imbalance and labeling errors (or class noise). Imbalanced data can make it more difficult for the neural network learning algorithms to distinguish between examples of the various classes, and class noise can lead to the formulation of incorrect hypotheses. Both class imbalance and labeling errors are pervasive problems encountered in a wide variety of application domains. Many studies have been performed to investigate these problems in isolation, but few have focused on their combined effects. This study presents a comprehensive empirical investigation using neural network algorithms to learn from imbalanced data with labeling errors. In particular, the first component of our study investigates the impact of class noise and class imbalance on two common neural network learning algorithms, while the second component considers the ability of data sampling (which is commonly used to address the issue of class imbalance) to improve their performances. Our results, for which over two million models were trained and evaluated, show that conclusions drawn using the more commonly studied C4.5 classifier may not apply when using neural networks.

Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts

Directory of Open Access Journals (Sweden)

Wolniakowski Adam

2018-03-01

Full Text Available The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method (Wolniakowski et al., 2013, 2015. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

Settlement of reactive power compensation in the light of white certificates

Directory of Open Access Journals (Sweden)

Zajkowski Konrad

2017-01-01

The detailed method and an estimation method proposed for the determination of savings on active energy as a result of the reactive power compensation carried out possess some errors and inconvenience. The detailed method requires knowledge of the network topology and a determination of reactive power Q at each point of the network. The estimation method of analysis is easy in execution, especially if the consumer of energy is the main or the most significant purchaser of electricity in the network. Unfortunately, this latter method can be used only for activities that do not require high computational accuracy. The results obtained by this method are approximate values that can be used for the calculation of economic indicators. The estimation method is suitable for determining the number of white certificates when a power audit concerns a recipient of electricity, the structure of which is a large number of divisions scattered at many different locations in the power system.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

Science.gov (United States)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

Antenna analysis using neural networks

Science.gov (United States)

Smith, William T.

1992-01-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

METHOD OF SOFTWARE-BASED COMPENSATION OF TECHNOLOGICAL VARIATION IN CHROMATICITY COORDINATES OF LCD PANELS

Directory of Open Access Journals (Sweden)

I. O. Zharinov

2015-05-01

Full Text Available Subject of research. The problem of software-based compensation of technological variation in chromaticity coordinates of liquid crystal panels is considered. A method of software-based compensation of technological variation in chromaticity coordinates is proposed. The method provides the color reproduction characteristics of the series-produced samples on-board indication equipment corresponding to the sample equipment, which is taken as the standard. Method. Mathematical calculation of the profile is performed for the given model of the liquid crystal panel. The coefficients that correspond to the typical values of the chromaticity coordinates for the vertices of the triangle color coverage constitute a reference mathematical model of the plate LCD panel from a specific manufacturer. At the stage of incoming inspection the sample of the liquid crystal panel, that is to be implemented within indication equipment, is mounted on the lighting test unit, where Nokia-Test control is provided by the formation of the RGB codes for display the image of a homogeneous field in the red, green, blue and white. The measurement of the (x,y-chromaticity coordinates in red, green, blue and white colors is performed using a colorimeter with the known value of absolute error. Instead of using lighting equipment, such measurements may be carried out immediately on the sample indication equipment during customizing procedure. The measured values are used to calculate individual LCD-panel profile coefficients through the use of Grassman's transformation, establishing mutual relations between the XYZ-color coordinates and RGB codes to be used for displaying the image on the liquid crystal panel. The obtained coefficients are to be set into the memory of the graphics controller together with the functional software and then used for image displaying. Main results. The efficiency of the proposed method of software-based compensation for technological variation of

Dynamic noise from action errors enhances network reciprocity in the prisoner's dilemma game

International Nuclear Information System (INIS)

Tanimoto, Jun; Ogasawara, Takashi

2015-01-01

Inspired by the fact that people make mistakes in a transient, fluctuating or chaotic environment, we establish a spatial prisoner's dilemma model where an agent commits action errors proportionally varying with the increasing/decreasing rate of the global cooperation fraction. A series of numerical simulations reveal that the cooperation level is enhanced in games in which the stag hunt (SH)-type dilemma is dominant; however, it is slightly diminished in games in which the chicken-type dilemma is dominant, compared with the standard network reciprocity model. Intensive analysis reveals that the noise created by the action error contribute to the spatial expansion of a cooperators' cluster, because a dilemma that is less chicken-type and more SH-type makes it disadvantageous for defectors to neighbor cooperators. Our finding, that errors in behavior in a chaotic environment contribute to the evolution of cooperation, might aim to explain the problem of how network reciprocity works. (paper)

Illumination compensation in ground based hyperspectral imaging

Science.gov (United States)

Wendel, Alexander; Underwood, James

2017-07-01

Hyperspectral imaging has emerged as an important tool for analysing vegetation data in agricultural applications. Recently, low altitude and ground based hyperspectral imaging solutions have come to the fore, providing very high resolution data for mapping and studying large areas of crops in detail. However, these platforms introduce a unique set of challenges that need to be overcome to ensure consistent, accurate and timely acquisition of data. One particular problem is dealing with changes in environmental illumination while operating with natural light under cloud cover, which can have considerable effects on spectral shape. In the past this has been commonly achieved by imaging known reference targets at the time of data acquisition, direct measurement of irradiance, or atmospheric modelling. While capturing a reference panel continuously or very frequently allows accurate compensation for illumination changes, this is often not practical with ground based platforms, and impossible in aerial applications. This paper examines the use of an autonomous unmanned ground vehicle (UGV) to gather high resolution hyperspectral imaging data of crops under natural illumination. A process of illumination compensation is performed to extract the inherent reflectance properties of the crops, despite variable illumination. This work adapts a previously developed subspace model approach to reflectance and illumination recovery. Though tested on a ground vehicle in this paper, it is applicable to low altitude unmanned aerial hyperspectral imagery also. The method uses occasional observations of reference panel training data from within the same or other datasets, which enables a practical field protocol that minimises in-field manual labour. This paper tests the new approach, comparing it against traditional methods. Several illumination compensation protocols for high volume ground based data collection are presented based on the results. The findings in this paper are

Framework of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

Xiaohua Tong

2014-05-01

Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

Neural Network based Minimization of BER in Multi-User Detection in SDMA

OpenAIRE

VENKATA REDDY METTU; KRISHAN KUMAR,; SRIKANTH PULLABHATLA

2011-01-01

In this paper we investigate the use of neural network based minimization of BER in MUD. Neural networks can be used for linear design, Adaptive prediction, Amplitude detection, Character Recognition and many other applications. Adaptive prediction is used in detecting the errors caused in AWGN channel. These errors are rectified by using Widrow-Hoff algorithm by updating their weights andAdaptive prediction methods. Both Widrow-Hoff and Adaptive prediction have been used for rectifying the e...

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Science.gov (United States)

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

A Modular Cascaded Multilevel Inverter Based Shunt Hybrid Active Power Filter for Selective Harmonic and Reactive Power Compensation Under Distorted/Unbalanced Grid Voltage Conditions

Directory of Open Access Journals (Sweden)

T. Demirdelen

2016-10-01

Full Text Available In recent years, shunt hybrid active power filters are being increasingly considered as a viable alternative to both passive filters and active power filters for compensating harmonics. In literature, their applications are restricted to balanced systems and low voltage applications and therefore not for industrial applications. This paper investigates the performance of a modular cascaded multilevel inverter based Shunt Hybrid Active Power Filter (SHAPF for reactive power compensation and selective harmonics elimination under distorted/unbalanced grid voltage conditions in medium voltage levels. In the proposed control method, reactive power compensation is achieved successfully with a perceptible amount and the performance results of harmonic compensation are satisfactory. Theoretical analysis and simulation results are obtained from an actual industrial network model in PSCAD. The simulation results are presented for a proposed system in order to demonstrate that the harmonic compensation performance meets the IEEE-519 standard.

A Multiple-Model Particle Filter Fusion Algorithm for GNSS/DR Slide Error Detection and Compensation

Directory of Open Access Journals (Sweden)

Rafael Toledo-Moreo

2018-03-01

Full Text Available Continuous accurate positioning is a key element for the deployment of many advanced driver assistance systems (ADAS and autonomous vehicle navigation. To achieve the necessary performance, global navigation satellite systems (GNSS must be combined with other technologies. A common onboard sensor-set that allows keeping the cost low, features the GNSS unit, odometry, and inertial sensors, such as a gyro. Odometry and inertial sensors compensate for GNSS flaws in many situations and, in normal conditions, their errors can be easily characterized, thus making the whole solution not only more accurate but also with more integrity. However, odometers do not behave properly when friction conditions make the tires slide. If not properly considered, the positioning perception will not be sound. This article introduces a hybridization approach that takes into consideration the sliding situations by means of a multiple model particle filter (MMPF. Tests with real datasets show the goodness of the proposal.

Induction motor IFOC based speed-controlled drive with asymptotic disturbance compensation

Directory of Open Access Journals (Sweden)

Stojić Đorđe M.

2012-01-01

Full Text Available This paper presents the design of digitally controlled speed electrical drive, with the asymptotic compensation of external disturbances, implemented by using the IFOC (Indirect Field Oriented Control torque controlled induction motor. The asymptotic disturbance compensation is achieved by using the DOB (Disturbance Observer with the IMP (Internal Model Principle. When compared to the existing IMP-based DOB solutions, in this paper the robust stability and disturbance compensation are improved by implementing the minimal order DOB filter. Also, the IMP-based DOB design is improved by employing the asymptotic compensation of all elemental or more complex external disturbances. The dynamic model of the IFOC torque electrical drive is, also, included in the speed-controller and DOB section design. The simulation and experimental measurements presented in the paper illustrate the effectiveness and robustness of the proposed control scheme.

voltage compensation using artificial neural network

African Journals Online (AJOL)

Offor Theophilos

Simulation results showed that DVR is effective in compensating for ... shutdown of heavy equipment, switching operations etc, ... station were carried out in MatLab 2013 application. ... semiconductor in a pulse width modulation (PWM).

Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

OpenAIRE

Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

2016-01-01

This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

Observability analysis of a MEMS INS/GPS integration system with gyroscope G-sensitivity errors.

Science.gov (United States)

Fan, Chen; Hu, Xiaoping; He, Xiaofeng; Tang, Kanghua; Luo, Bing

2014-08-28

Gyroscopes based on micro-electromechanical system (MEMS) technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS) and the Global Positioning System (GPS). The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously.

Observability Analysis of a MEMS INS/GPS Integration System with Gyroscope G-Sensitivity Errors

Directory of Open Access Journals (Sweden)

Chen Fan

2014-08-01

Full Text Available Gyroscopes based on micro-electromechanical system (MEMS technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS and the Global Positioning System (GPS. The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously.

Whiplash and the compensation hypothesis.

Science.gov (United States)

Spearing, Natalie M; Connelly, Luke B

2011-12-01

Review article. To explain why the evidence that compensation-related factors lead to worse health outcomes is not compelling, either in general, or in the specific case of whiplash. There is a common view that compensation-related factors lead to worse health outcomes ("the compensation hypothesis"), despite the presence of important, and unresolved sources of bias. The empirical evidence on this question has ramifications for the design of compensation schemes. Using studies on whiplash, this article outlines the methodological problems that impede attempts to confirm or refute the compensation hypothesis. Compensation studies are prone to measurement bias, reverse causation bias, and selection bias. Errors in measurement are largely due to the latent nature of whiplash injuries and health itself, a lack of clarity over the unit of measurement (specific factors, or "compensation"), and a lack of appreciation for the heterogeneous qualities of compensation-related factors and schemes. There has been a failure to acknowledge and empirically address reverse causation bias, or the likelihood that poor health influences the decision to pursue compensation: it is unclear if compensation is a cause or a consequence of poor health, or both. Finally, unresolved selection bias (and hence, confounding) is evident in longitudinal studies and natural experiments. In both cases, between-group differences have not been addressed convincingly. The nature of the relationship between compensation-related factors and health is unclear. Current approaches to testing the compensation hypothesis are prone to several important sources of bias, which compromise the validity of their results. Methods that explicitly test the hypothesis and establish whether or not a causal relationship exists between compensation factors and prolonged whiplash symptoms are needed in future studies.

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

Science.gov (United States)

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Application for vibration monitoring of aspheric surface machining based on wireless sensor networks

Science.gov (United States)

Han, Chun Guang; Guo, Yin Biao; Jiang, Chen

2010-05-01

Any kinds of tiny vibration of machine tool parts will have a great influence on surface quality of the workpiece at ultra-precise machining process of aspheric surface. At present the major way for decreasing influence of vibration is machining compensation technology. Therefore it is important for machining compensation control to acquire and transmit these vibration signals effectively. This paper presents a vibration monitoring system of aspheric surface machining machine tool based on wireless sensor networks (WSN). Some key issues of wireless sensor networks for vibration monitoring system of aspheric surface machining are discussed. The reliability of data transmission, network communication protocol and synchronization mechanism of wireless sensor networks are studied for the vibration monitoring system. The proposed system achieves multi-sensors vibration monitoring involving the grinding wheel, the workpiece and the workbench spindle. The wireless transmission of vibration signals is achieved by the combination with vibration sensor nodes and wireless network. In this paper, these vibration sensor nodes are developed. An experimental platform is structured which employs wireless sensor networks to the vibration monitoring system in order to test acquisition and wireless transmission of vibration signal. The test results show that the proposed system can achieve vibration data transmission effectively and reliability and meet the monitoring requirements of aspheric surface machining machine tool.

Marine Ecological Environment Management Based on Ecological Compensation Mechanisms

Directory of Open Access Journals (Sweden)

Qunzhen Qu

2016-12-01

Full Text Available The level of marine environmental management is a key factor in the successful implementation of marine power strategies. The improvement in management levels of marine environments requires innovation in marine management. In other words, the transformation of marine environmental management into marine ecological environment management must be done in order to achieve sustainable development of the marine economy. As an environmental economic policy that combines both administrative and market measures, ecological compensation mechanisms have significant advantages in marine ecological environment management. Based on the study of the current development of ecological compensation mechanisms in China, through the analysis of the connotation of marine ecological civilization, existing marine ecological protection practices and marine environmental management methods, this paper posits that the current marine ecological environment management in China should be established on the basis of ecological compensation mechanisms. At present, a lack of laws and regulations for overall marine ecological environment management is the key factor restricting the practice of marine ecological environment management. Therefore, it is necessary to explore the current path of marine ecological environment management in China from the perspective of the construction of legal system of ecological compensation law, the establishment of ecological compensation fees, ecological taxes and ecological compensation fund systems, and the clear status for a marine ecological management and supervision body.

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

Science.gov (United States)

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Calibration and compensation of deflections and compliances in remote handling equipment configurations

International Nuclear Information System (INIS)

Kivelae, Tuomo; Saarinen, H.; Mattila, J.; Haemaelaeinen, V.; Siuko, M.; Semeraro, L.

2011-01-01

This paper presents a generic method of calibrating and compensating remote handling system configurations subject to manufacturing and assembly tolerances, deflections and compliances. A method consists of kinematic part and non-kinematic part. A kinematic calibration algorithm is presented for finding the values of kinematic model errors by measuring the end-effector Cartesian position. This is a conventional way to calibrate industrial robots. However, in this case the kinematic calibration is not able to compensate flaws fully due to large deflections and compliances caused by a massive Cassette payload (approx. 9 ton). Positioning error at the furthest point of the cassette before any compensation was 80 mm. Therefore, extra compensation must be introduced in addition to a kinematic calibration. A kinematic calibration together with an extra compensation is a demanding task to carry out. The resulting complex compensation function has to be such that it can be implemented in real-time Cassette Multifunctional Mover (CMM) control system software.

Optimal Meter Placement for Distribution Network State Estimation: A Circuit Representation Based MILP Approach

DEFF Research Database (Denmark)

Chen, Xiaoshuang; Lin, Jin; Wan, Can

2016-01-01

State estimation (SE) in distribution networks is not as accurate as that in transmission networks. Traditionally, distribution networks (DNs) are lack of direct measurements due to the limitations of investments and the difficulties of maintenance. Therefore, it is critical to improve the accuracy...... of SE in distribution networks by placing additional physical meters. For state-of-the-art SE models, it is difficult to clearly quantify measurements' influences on SE errors, so the problems of optimal meter placement for reducing SE errors are mostly solved by heuristic or suboptimal algorithms....... Under this background, this paper proposes a circuit representation model to represent SE errors. Based on the matrix formulation of the circuit representation model, the problem of optimal meter placement can be transformed to a mixed integer linear programming problem (MILP) via the disjunctive model...

Correction method for the error of diamond tool's radius in ultra-precision cutting

Science.gov (United States)

Wang, Yi; Yu, Jing-chi

2010-10-01

The compensation method for the error of diamond tool's cutting edge is a bottle-neck technology to hinder the high accuracy aspheric surface's directly formation after single diamond turning. Traditional compensation was done according to the measurement result from profile meter, which took long measurement time and caused low processing efficiency. A new compensation method was firstly put forward in the article, in which the correction of the error of diamond tool's cutting edge was done according to measurement result from digital interferometer. First, detailed theoretical calculation related with compensation method was deduced. Then, the effect after compensation was simulated by computer. Finally, φ50 mm work piece finished its diamond turning and new correction turning under Nanotech 250. Testing surface achieved high shape accuracy pv 0.137λ and rms=0.011λ, which approved the new compensation method agreed with predictive analysis, high accuracy and fast speed of error convergence.

Methodes de compensation des erreurs d'usinage utilisant la mesure sur machines-outils

Science.gov (United States)

Guiassa, Rachid

On-machine measurement process is used to inspect the part immediately after the cut without part removal and additional setups. It detects the machining defects visible to the machine tool. The system machine-tool-part deflection and the cutting tool dimension inaccuracy are the most important sources of these defects. The machined part can be inspected, at the semi-finishing cut level to identify systematic defects that may occur later at the finishing cut. Therefore, corrective actions can be derived to anticipate the expected error in order to produce a part with acceptable accuracy. For industrial profitability, the measurement and the compensation tasks must be done under the closed door machining requirement without human interventions. This thesis aims to develop mathematical models that use the data inspection of previous cuts to formulate the compensation of the finishing-cut. The goal of the compensation is to anticipate the expected error which is identified under two components. One is independent on the depth of cut and is related to the cutting tool dimension such as the wear. The other is dependent on the cutting depth such as the deflection. A general model is presented which relies solely on-machine probing data from semi-finishing cuts to compensate the final cut. A variable cutting compliance coefficient relates the total system deflection to the depth of cut in multi-cut process. It is used to estimate the compensation of the tool path. The model is able to take into account the effect of the cutting depth variation and the material removal in the estimation of the error at the finishing-cut. In order to generate the continuous compensated tool path from discrete measurements, a B-Spline deformation technique is adapted to the available data and applied to compute the compensated tool path according to a restricted number of discrete compensation vectors. The results show that the on-machine probed errors can be significantly reduced using the

Disturbance estimation and compensation for planar motors on the long-stroke stage of a wafer stage

Directory of Open Access Journals (Sweden)

Bizhong Xia

2015-04-01

Full Text Available This article presents a data-based method to estimate and compensate low-frequency disturbance in planar motors on the long-stroke stage of a wafer stage, which is a typical multiple-input multiple-output system. First, a data-based method is introduced to decouple the multiple-input multiple-output system into multi-single-input single-output system, which is crucial for the design of controller and the correction of disturbance estimation in the scanning direction. Second, dominant low-frequency disturbances in the long-stroke stage are analyzed. Third, estimation and compensation method under moving condition is proposed. The compensation method is based on three feedforward tables, and the tables are indexed by trajectory parameters, including velocity and position instead of time in the iterative learning control method. Finally, experiments are performed on the long-stroke stage of a wafer stage to verify the proposed method. Experimental results show that the proposed method can effectively improve the servo performance by reducing the tracking errors by nearly 1/2 in the forward direction and 1/3 in the backward direction and lowering error difference between the forward and backward directions from 5.1 to 1.2 µm.

Active power compensator of the current harmonics based on the instantaneous power theory

Directory of Open Access Journals (Sweden)

Marian GAICEANU

2005-12-01

Full Text Available The quality of the electrical current becomes a major concern. The proliferation of the power electronic converters, which are used extensively to control electrical apparatus in industrial and commercial applications (dc and ac variable speed motor drives, induction furnaces, power line conditioners, and industrial power supplies, is at the origin of the AC current distribution network pollution and the reactive power demand. These power electronic converters typically draw non-sinusoidal currents from the utility, causing interference with adjacent sensitive loads and limit the utilization of the available electrical supply. The quality of the electrical current thus becomes a significant concern for the distributors of energy and their customers. Recent progress as regards technology of the power electronics brings a capacity of compensation and correction of the harmonic distortion generated by the nonlinear loads. In this paper a parallel active filter prototype capable of reducing the total harmonic distortion in the supply for most current source or adjustable speed drive type loads is presented. A 33 kVA active power filter was developed for harmonic and reactive power compensation based on the instantaneous power theory. The active filter configuration requires the measurement of both the load and filter currents. Experimental results from a prototype active power filter confirm the suitability of the proposed approach. The actual 33kVA prototype converter has been built and tested in the SIEI S.p.A. (Italy laboratory under the Marie Curie Post Doctoral research. The active power compensator is controlled by a high performance DSP platform, resulting in the following active filter features: source current reduction up to the 25th harmonic, 10% THD achievable for current source type loads, efficiency above 97%, does not cause resonance with other loads, operation in the presence of unbalanced loads, reactive power and harmonics

Research on the compensation of laser launch optics to improve the performance of the LGS spot.

Science.gov (United States)

Liu, Jie; Wang, Jianli; Wang, Yuning; Tian, Donghe; Zheng, Quan; Lin, Xudong; Wang, Liang; Yang, Qingyun

2018-02-01

To improve the beam quality of the uplink laser, a 37 channel piezo-ceramic deformable mirror was inserted into the laser launch optics to compensate the static aberrations. An interferometer was used as the calibration light source as well as the wavefront sensor to perform closed-loop correction for the moment. About 0.38λ root mean square (rms) aberrations, including the deformable mirror's initial figure error, were compensated, and the residual error was less than 0.07λ rms. Field observations with a 2 m optical telescope demonstrated that the peak intensity value of the laser guide star (LGS) spot increased from 5650 to 7658, and the full width at half-maximum (FWHM) size reduced from 4.07 arcseconds to 3.52 arcseconds. With the compensation, an improved guide star spot can be obtained, which is crucial for the adaptive optics systems of ground-based large telescopes.

On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

Directory of Open Access Journals (Sweden)

Saikat Kumar Shome

2015-01-01

Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

DC-Compensated Current Transformer †

Science.gov (United States)

Ripka, Pavel; Draxler, Karel; Styblíková, Renata

2016-01-01

Instrument current transformers (CTs) measure AC currents. The DC component in the measured current can saturate the transformer and cause gross error. We use fluxgate detection and digital feedback compensation of the DC flux to suppress the overall error to 0.15%. This concept can be used not only for high-end CTs with a nanocrystalline core, but it also works for low-cost CTs with FeSi cores. The method described here allows simultaneous measurements of the DC current component. PMID:26805830

Increasing of AC compensation method accuracy

International Nuclear Information System (INIS)

Havlicek, V.; Pokorny, M.

2003-01-01

The original MMF compensation method allows the magnetic properties of single sheets and strips to be measured in the same way as the closed specimen properties. The accuracy of the method is limited due to the finite gain of the feedback loop fulfilling the condition of its stability. Digitalisation of the compensation loop appropriate processing of the error signal can rapidly improve the accuracy. The basic ideas of this new approach and the experimental results are described in this paper

Increasing of AC compensation method accuracy

Science.gov (United States)

Havlíček, V.; Pokorný, M.

2003-01-01

The original MMF compensation method allows the magnetic properties of single sheets and strips to be measured in the same way as the closed specimen properties. The accuracy of the method is limited due to the finite gain of the feedback loop fulfilling the condition of its stability. Digitalisation of the compensation loop appropriate processing of the error signal can rapidly improve the accuracy. The basic ideas of this new approach and the experimental results are described in this paper.

Hybrid VAR compensator with improved efficiency

Directory of Open Access Journals (Sweden)

V. V. Burlaka

2015-03-01

Full Text Available In modern electrical networks thyristor-switched capacitors (TSC are most used devices for VAR compensation. These devices don’t contain rotating parts and mechanical contacts, provide a stepwise control of reactive power and no generation of harmonics to the network. However, with the help of TSC it’s not possible to ensure smooth control of reactive power and capacitor banks (CB are exposed to the negative impact of higher harmonic components of the network voltage. Hybrid VAR compensator don’t have such drawbacks. It consists of active filter (AF and capacitor bank with discrete regulation. The main drawback of such systems is the necessity of accessing all six terminals of CB, while most of them are manufactured with three terminals, internally delta-connected. In the article, the topology and control system of hybrid VAR compensator free from beforementioned drawback, is proposed. The control system provides operating modes of overcompensation or undercompensation reactive power. VAR distribution regulator performs redistribution of reactive power between active filter and capacitor banks with the condition to minimize active filter’s power. Scheme of the hybrid VAR compensator, which includes a three-phase three-terminal delta-connected capacitor banks, is shown. Proposed approach allows to provide smooth control of reactive power, isolate the capacitor bank from harmonic currents and use a more effective low-voltage power components

Negligence, genuine error, and litigation

Directory of Open Access Journals (Sweden)

Sohn DH

2013-02-01

Full Text Available David H SohnDepartment of Orthopedic Surgery, University of Toledo Medical Center, Toledo, OH, USAAbstract: Not all medical injuries are the result of negligence. In fact, most medical injuries are the result either of the inherent risk in the practice of medicine, or due to system errors, which cannot be prevented simply through fear of disciplinary action. This paper will discuss the differences between adverse events, negligence, and system errors; the current medical malpractice tort system in the United States; and review current and future solutions, including medical malpractice reform, alternative dispute resolution, health courts, and no-fault compensation systems. The current political environment favors investigation of non-cap tort reform remedies; investment into more rational oversight systems, such as health courts or no-fault systems may reap both quantitative and qualitative benefits for a less costly and safer health system.Keywords: medical malpractice, tort reform, no fault compensation, alternative dispute resolution, system errors

Intelligent measurement and compensation of linear motor force ripple: a projection-based learning approach in the presence of noise

Science.gov (United States)

Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin

2018-06-01

Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.

Neural network based adaptive control for nonlinear dynamic regimes

Science.gov (United States)

Shin, Yoonghyun

Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

Reward-based training of recurrent neural networks for cognitive and value-based tasks.

Science.gov (United States)

Song, H Francis; Yang, Guangyu R; Wang, Xiao-Jing

2017-01-13

Trained neural network models, which exhibit features of neural activity recorded from behaving animals, may provide insights into the circuit mechanisms of cognitive functions through systematic analysis of network activity and connectivity. However, in contrast to the graded error signals commonly used to train networks through supervised learning, animals learn from reward feedback on definite actions through reinforcement learning. Reward maximization is particularly relevant when optimal behavior depends on an animal's internal judgment of confidence or subjective preferences. Here, we implement reward-based training of recurrent neural networks in which a value network guides learning by using the activity of the decision network to predict future reward. We show that such models capture behavioral and electrophysiological findings from well-known experimental paradigms. Our work provides a unified framework for investigating diverse cognitive and value-based computations, and predicts a role for value representation that is essential for learning, but not executing, a task.

Robotic motion compensation for applications in radiation oncology

Energy Technology Data Exchange (ETDEWEB)

Herrmann, Christian

2013-07-22

introduced fusing both breathing and tumor position information to allow for predictions without the need of an explicit correlation model. Predictions determine the future motion path of the HexaPOD in order to compensate for tumor motion. Several control schemes are developed to enable reference tracking for the HexaPOD. Based on linear and non-linear dynamic modelling of the HexaPOD with system identification methods, a first controller is derived in the form of a model predictive controller. A second controller is proposed based on an assumption of the working principle of the HexaPOD's internal controller. Finally, a third controller is derived as combination of the first and second one. For each of these controllers, comparative results with real hardware experiments and humans in the loop as well as choices of free parameters are presented and discussed. Apart from precise tracking, emphasis is placed on patient comfort which is of crucial importance for acceptance of the system. It is demonstrated that smooth trajectories can be realized by the controllers to guarantee that patients feel comfortable while their tumor motion is compensated at sub-millimeter accuracies. Overall errors of the system are analyzed by relating them to tracking and prediction errors. By exploiting the properties of different predictors, it is shown that the startup time until tracking is reached can be reduced to only a few seconds, even in the case of an initially at-rest HexaPOD and with no initial knowledge of tumor motion. This makes the system especially suitable for the relatively short-fractionated treatment sessions for lung tumors. The tumor motion compensation system has been developed solely based on standard clinical hardware, found in most treatment rooms. With a simple and flexible design, existing treatment can be updated in a cost-efficient way to introduce motion compensation capabilities. Simultaneously, the system does not impose any constraints on state

Robotic motion compensation for applications in radiation oncology

International Nuclear Information System (INIS)

Herrmann, Christian

2013-01-01

introduced fusing both breathing and tumor position information to allow for predictions without the need of an explicit correlation model. Predictions determine the future motion path of the HexaPOD in order to compensate for tumor motion. Several control schemes are developed to enable reference tracking for the HexaPOD. Based on linear and non-linear dynamic modelling of the HexaPOD with system identification methods, a first controller is derived in the form of a model predictive controller. A second controller is proposed based on an assumption of the working principle of the HexaPOD's internal controller. Finally, a third controller is derived as combination of the first and second one. For each of these controllers, comparative results with real hardware experiments and humans in the loop as well as choices of free parameters are presented and discussed. Apart from precise tracking, emphasis is placed on patient comfort which is of crucial importance for acceptance of the system. It is demonstrated that smooth trajectories can be realized by the controllers to guarantee that patients feel comfortable while their tumor motion is compensated at sub-millimeter accuracies. Overall errors of the system are analyzed by relating them to tracking and prediction errors. By exploiting the properties of different predictors, it is shown that the startup time until tracking is reached can be reduced to only a few seconds, even in the case of an initially at-rest HexaPOD and with no initial knowledge of tumor motion. This makes the system especially suitable for the relatively short-fractionated treatment sessions for lung tumors. The tumor motion compensation system has been developed solely based on standard clinical hardware, found in most treatment rooms. With a simple and flexible design, existing treatment can be updated in a cost-efficient way to introduce motion compensation capabilities. Simultaneously, the system does not impose any constraints on state

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm

Directory of Open Access Journals (Sweden)

Man Zhang

2017-10-01

Full Text Available Precise azimuth-variant motion compensation (MOCO is an essential and difficult task for high-resolution synthetic aperture radar (SAR imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA, have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Standard compensation for power cuts. Working group report

International Nuclear Information System (INIS)

2002-07-01

The Working Group was commissioned to draw up a proposal in the form of a Government Bill for provisions to be included in the Electricity Market Act on imposing an obligation on the distribution net operator to pay a standard compensation to the users of electricity for the event that they get no access to electricity. The Working Group should consider especially a model of standard compensation presented in the final report by Mr. Jarl Forsten, Deputy Director General of the Technical Research Centre of Finland VTT, published on 30 April 2002 that the amount of standard compensation should not depend on the reason for the power cut. The Working Group proposes that the Electricity Market Act should be amended by provisions providing that a distribution net operator shall pay to the user of electricity a standard compensation for power cuts lasting over 12 hours. The amount of compensation shall be based on the annual network service fee and a sliding scale of compensation related to the duration of the power cut shall be applied. The maximum compensation shall be paid when the power cut lasts more than five days. The maximum amount of individual compensations shall be fixed at EUR 700. The proposed provisions on standard compensation in the event of power cuts are aimed at amending the provisions in Chapter 6a of the Electricity Market Act on price reduction and compensation because of fault in the supply of electricity. The aim of the introduction of standard compensation for power cuts is to persuade distribution net operators to make an effort to minimize the time for power cuts. (orig.)

Group representations, error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E

1996-01-01

This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

Hysteresis Compensation of Piezoresistive Carbon Nanotube/Polydimethylsiloxane Composite-Based Force Sensors

Directory of Open Access Journals (Sweden)

Ji-Sik Kim

2017-01-01

Full Text Available This paper provides a preliminary study on the hysteresis compensation of a piezoresistive silicon-based polymer composite, poly(dimethylsiloxane dispersed with carbon nanotubes (CNTs, to demonstrate its feasibility as a conductive composite (i.e., a force-sensitive resistor for force sensors. In this study, the potential use of the nanotube/polydimethylsiloxane (CNT/PDMS as a force sensor is evaluated for the first time. The experimental results show that the electrical resistance of the CNT/PDMS composite changes in response to sinusoidal loading and static compressive load. The compensated output based on the Duhem hysteresis model shows a linear relationship. This simple hysteresis model can compensate for the nonlinear frequency-dependent hysteresis phenomenon when a dynamic sinusoidal force input is applied.

Designing magnetic compensated states in tetragonal Mn{sub 3}Ge-based Heusler alloys

Energy Technology Data Exchange (ETDEWEB)

You, Yurong; Xu, Guizhou, E-mail: gzxu@njust.edu.cn; Hu, Fang; Gong, Yuanyuan; Liu, Er; Peng, Guo; Xu, Feng, E-mail: xufeng@njust.edu.cn

2017-05-01

Magnetic compensated materials attracted much interests due to the observed large exchange bias and large coercivity, and also their potential applications in the antiferromagnetic spintronics with merit of no stray field. In this work, by using ab-initio studies, we designed several Ni (Pd, Pt) doped Mn{sub 3}Ge-based D0{sub 22}-type tetragonal Heusler alloys with fully compensated states. Theoretically, we find the total moment change is asymmetric across the compensation point (at ~x=0.3) in Mn{sub 3-x}Y{sub x}Ge (Y=Ni, Pd, Pt). In addition, an uncommon discontinuous jump is observed across the critical zero-moment point, indicating that some non-trivial properties may emerge at this point. Further electronic analyses of these compensated alloys reveal high spin polarizations at the Fermi level, which is advantageous for spin transfer torque applications. - Highlights: • Several new fully compensated magnetic states are identified in Mn{sub 3}Ge-based tetragonal alloys. • The magnetic moment changes are asymmetric upon Ni, Pd and Pt substitution. • Discontinuous jumps exist across the compensated points. • The three compensated alloys possess large spin polarizations.

Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system.

Science.gov (United States)

Guo, Xiaoting; Sun, Changku; Wang, Peng

2017-08-01

This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

Numerical Analysis of Modeling Based on Improved Elman Neural Network

Directory of Open Access Journals (Sweden)

Shao Jie

2014-01-01

Full Text Available A modeling based on the improved Elman neural network (IENN is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL model, Chebyshev neural network (CNN model, and basic Elman neural network (BENN model, the proposed model has better performance.

A dynamic compensation method for natural ambient dose rate based on 6 years data from the Dutch radioactivity monitoring network

International Nuclear Information System (INIS)

Smetsers, R.C.G.M.; Blaauboer, R.O.

1997-01-01

The significant variations in time exhibited by background radiation hinders a sensitive recognition of human-induced factors. A comprehensive study in the Netherlands has examined the influence of the various natural processes on the natural background using six years data from the Dutch nuclear emergency network. Results presented concentrate on temporal variations in ambient dose-equivalent rate, H*(10), and have led to simple expressions to model the ambient dose rate using a limited set of readily available parameters, i.e. air pressure, deposition rate and equilibrium equivalent decay product concentration of 222 Rn, EEDC. Best values and uncertainty ranges of the applied parameters are reported. Remaining variations, e.g. due to variations in the cosmic radiation intensity and the radon soil profile, are shown to be small in the Netherlands, with one exception when the cosmogenic dose rate at sea level was decreased for a period of months due to a global deflection of the earth's magnetic field in the summer of 1991. The resulting compensation method for the natural ambient dose rate enables sensitive detection of anomalies, supporting the surveillance of nuclear installations and the management of nuclear emergency networks. (Author)

Study of SPM tolerances of electronically compensated DML based systems.

Science.gov (United States)

Papagiannakis, I; Klonidis, D; Birbas, Alexios N; Kikidis, J; Tomkos, I

2009-05-25

This paper experimentally investigates the effectiveness of electronic dispersion compensation (EDC) for signals limited by self phase modulation (SPM) and various dispersion levels. The sources considered are low-cost conventional directly modulated lasers (DMLs), fabricated for operation at 2.5 Gb/s but modulated at 10 Gb/s. Performance improvement is achieved by means of electronic feed-forward and decision-feedback equalization (FFE/DFE) at the receiver end. Experimental studies consider both transient and adiabatic chirp dominated DMLs sources. The improvement is evaluated in terms of required optical signal-to-noise ratio (ROSNR) for bit-error-rate (BER) values of 10(-3) versus launch power over uncompensated links of standard single mode fiber (SSMF).

The Evolution of Reputation-Based Cooperation in Regular Networks

Directory of Open Access Journals (Sweden)

Tatsuya Sasaki

2017-01-01

Full Text Available Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules—shunning, image scoring, stern judging, and simple standing—and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule—simple standing—is the most robust among the four assessment rules in promoting cooperation in regular networks.

A High Efficiency Charging Strategy for a Supercapacitor Using a Wireless Power Transfer System Based on Inductor/Capacitor/Capacitor (LCC Compensation Topology

Directory of Open Access Journals (Sweden)

Yuyu Geng

2017-01-01

Full Text Available In the application of rail transit vehicles, when using typical wireless power transfer (WPT systems with series–series (SS compensation supply power for supercapacitors, the output current is in an approximately inverse relationship with the duty cycle in a wide range. This renders the typical buck circuit control inappropriate. In order to help resolve the above issues, this paper designs inductor/capacitor/capacitor (LCC compensation with new compensation parameters, which can achieve an adjustable quasi-constant voltage from the input of the inverter to the output of the rectifier. In addition, the two-port network method is used to analyze the resonant compensation circuit. The analysis shows that LCC compensation is more suitable for the WPT system using the supercapacitor as the energy storage device. In the case of LCC compensation topology combined with the charging characteristics of the supercapacitor, an efficient charging strategy is designed, namely first constant current charging, followed by constant power charging. Based on the analysis of LCC compensation, the system has an optimal load, by which the system works at the maximum efficiency point. Combined with the characteristics of the constant voltage output, the system can maintain high efficiency in the constant power stage by making constant output power the same as the optimal power point. Finally, the above design is verified through experiments.

The NASA F-15 Intelligent Flight Control Systems: Generation II

Science.gov (United States)

Buschbacher, Mark; Bosworth, John

2006-01-01

The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

Tracking control of a closed-chain five-bar robot with two degrees of freedom by integration of an approximation-based approach and mechanical design.

Science.gov (United States)

Cheng, Long; Hou, Zeng-Guang; Tan, Min; Zhang, W J

2012-10-01

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.

Manufacturing error sensitivity analysis and optimal design method of cable-network antenna structures

Science.gov (United States)

Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye

2016-03-01

Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.

Adaptive online state-of-charge determination based on neuro-controller and neural network

Energy Technology Data Exchange (ETDEWEB)

Shen Yanqing, E-mail: network_hawk@126.co [Department of Automation, Chongqing Industry Polytechnic College, Jiulongpo District, Chongqing 400050 (China)

2010-05-15

This paper presents a novel approach using adaptive artificial neural network based model and neuro-controller for online cell State of Charge (SOC) determination. Taking cell SOC as model's predictive control input unit, radial basis function neural network, which can adjust its structure to prediction error with recursive least square algorithm, is used to simulate battery system. Besides that, neuro-controller based on Back-Propagation Neural Network (BPNN) and modified PID controller is used to decide the control input of battery system, i.e., cell SOC. Finally this algorithm is applied for the SOC determination of lead-acid batteries, and results of lab tests on physical cells, compared with model prediction, are presented. Results show that the ANN based battery system model adaptively simulates battery system with great accuracy, and the predicted SOC simultaneously converges to the real value quickly within the error of +-1 as time goes on.

Cooperative MIMO Communication at Wireless Sensor Network: An Error Correcting Code Approach

Science.gov (United States)

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error pb. It is observed that C-MIMO performs more efficiently when the targeted pb is smaller. Also the lower encoding rate for LDPC code offers better error characteristics. PMID:22163732

Cooperative MIMO communication at wireless sensor network: an error correcting code approach.

Science.gov (United States)

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error p(b). It is observed that C-MIMO performs more efficiently when the targeted p(b) is smaller. Also the lower encoding rate for LDPC code offers better error characteristics.

Development of Fast Error Compensation Algorithm for Integrated Inertial-Satellite Navigation System of Small-size Unmanned Aerial Vehicles in Complex Environment

Directory of Open Access Journals (Sweden)

A. V. Fomichev

2015-01-01

Full Text Available In accordance with the structural features of small-size unmanned aerial vehicle (UAV, and considering the feasibility of this project, the article studies an integrated inertial-satellite navigation system (INS. The INS algorithm development is based on the method of indirect filtration and principle of loosely coupled combination of output data on UAV positions and velocity. Data on position and velocity are provided from the strapdown inertial navigation system (SINS and satellite navigation system (GPS. A difference between the output flows of measuring data on position and velocity provided from the SINS and GPS is used to evaluate SINS errors by means of the basic algorithm of Kalman filtering. Then the outputs of SINS are revised. The INS possesses the following advantages: a simpler mathematical model of Kalman filtering, high reliability, two independently operating navigation systems, and high redundancy of available navigation information.But in case of loosely coupled scheme, INS can meet the challenge of high precision and reliability of navigation only when the SINS and GPS operating conditions are normal all the time. The proposed INS is used with UAV moving in complex environment due to obstacles available, severe natural climatic conditions, etc. This case expects that it is impossible for UAV to receive successful GPS-signals frequently. In order to solve this problem, was developed an algorithm for rapid compensation for errors of INS information, which could effectively solve the problem of failure of the navigation system in case there are no GPS-signals .Since it is almost impossible to obtain the data of the real trajectory in practice, in the course of simulation in accordance with the kinematic model of the UAV and the complex environment of the terrain, the flight path generator is used to produce the flight path. The errors of positions and velocities are considered as an indicator of the INS effectiveness. The results

Compensator design for hysteresis of a stacked PZT actuator using a congruency-based hysteresis model

International Nuclear Information System (INIS)

Nguyen, Phuong-Bac; Choi, Seung-Bok

2012-01-01

This paper proposes a rate-independent hysteresis compensator for a stacked PZT (lead zirconate titanate) actuator. From a congruency-based hysteresis (CBH) model which is derived from the inherent properties of this actuator, especially the congruency, a feedforward compensator associated with it is developed. The formulation of the proposed compensator is based on an assumption that the inverse operator also possesses the same properties as the CBH model does. This implies that the compensator also possesses properties such as the wiped-out loop closing between the consecutive control points and congruency. Consequently, the expressions for the compensator can be conducted by exploiting the equations for the CBH model in two cases of monotonic increase and monotonic decrease of input excitation. In order to assess the performance of the compensator, several experiments in both open-loop and closed-loop controls are undertaken. In the open-loop control experiment, the performance of the feedforward compensator using the CBH model is compared with the classical Preisach model-based one in three cases of reference waveforms. In the closed-loop control experiment, the proposed compensator is incorporated into a PID (proportional-integral-derivative) control system and the performance of this integrated system is then evaluated and compared to that of the PID with and without compensator. (paper)

Efficient Vector-Based Forwarding for Underwater Sensor Networks

Directory of Open Access Journals (Sweden)

Peng Xie

2010-01-01

Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

Settlement of reactive power compensation in the light of white certificates

Science.gov (United States)

Zajkowski, Konrad

2017-10-01

The article discusses the problem of the determination of savings on active energy as a result of a reactive power compensation. Statutory guidance on the required energy audit to obtain white certificates in the European Union was followed. The analysis was made on the basis of the Polish Law. The paper presents a detailed analytical method and an estimation method taking into account the impact on the line, the transformer and the generator. According to the relevant guidelines in the European Union, the reduction of CO2 emissions by calculating the saving of active power should be determined. The detailed method and an estimation method proposed for the determination of savings on active energy as a result of the reactive power compensation carried out possess some errors and inconvenience. The detailed method requires knowledge of the network topology and a determination of reactive power Q at each point of the network. The estimation method of analysis is easy in execution, especially if the consumer of energy is the main or the most significant purchaser of electricity in the network. Unfortunately, this latter method can be used only for activities that do not require high computational accuracy. The results obtained by this method are approximate values that can be used for the calculation of economic indicators. The estimation method is suitable for determining the number of white certificates when a power audit concerns a recipient of electricity, the structure of which is a large number of divisions scattered at many different locations in the power system.

The "Measuring Outcomes of Clinical Connectivity" (MOCC) trial: investigating data entry errors in the Electronic Primary Care Research Network (ePCRN).

Science.gov (United States)

Fontaine, Patricia; Mendenhall, Tai J; Peterson, Kevin; Speedie, Stuart M

2007-01-01

The electronic Primary Care Research Network (ePCRN) enrolled PBRN researchers in a feasibility trial to test the functionality of the network's electronic architecture and investigate error rates associated with two data entry strategies used in clinical trials. PBRN physicians and research assistants who registered with the ePCRN were eligible to participate. After online consent and randomization, participants viewed simulated patient records, presented as either abstracted data (short form) or progress notes (long form). Participants transcribed 50 data elements onto electronic case report forms (CRFs) without integrated field restrictions. Data errors were analyzed. Ten geographically dispersed PBRNs enrolled 100 members and completed the study in less than 7 weeks. The estimated overall error rate if field restrictions had been applied was 2.3%. Participants entering data from the short form had a higher rate of correctly entered data fields (94.5% vs 90.8%, P = .004) and significantly more error-free records (P = .003). Feasibility outcomes integral to completion of an Internet-based, multisite study were successfully achieved. Further development of programmable electronic safeguards is indicated. The error analysis conducted in this study will aid design of specific field restrictions for electronic CRFs, an important component of clinical trial management systems.

Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation

Directory of Open Access Journals (Sweden)

Yuzheng Yang

2014-01-01

Full Text Available An adaptive sliding controller using radial basis function (RBF network to approximate the unknown system dynamics microelectromechanical systems (MEMS gyroscope sensor is proposed. Neural controller is proposed to approximate the unknown system model and sliding controller is employed to eliminate the approximation error and attenuate the model uncertainties and external disturbances. Online neural network (NN weight tuning algorithms, including correction terms, are designed based on Lyapunov stability theory, which can guarantee bounded tracking errors as well as bounded NN weights. The tracking error bound can be made arbitrarily small by increasing a certain feedback gain. Numerical simulation for a MEMS angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive neural control scheme and demonstrate the satisfactory tracking performance and robustness.

Robust Position Tracking for Electro-Hydraulic Drives Based on Generalized Feedforward Compensation Approach

DEFF Research Database (Denmark)

Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

2012-01-01

This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and...... constant gain type feedforward compensator, when subjected to strong perturbations in supply pressure and coulomb friction....

Rotor Field Oriented Control with adaptive Iron Loss Compensation

DEFF Research Database (Denmark)

Rasmussen, Henrik; Vadstrup, P.; Børsting, H.

1999-01-01

It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model...... controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....

Correlated measurement error hampers association network inference

NARCIS (Netherlands)

Kaduk, M.; Hoefsloot, H.C.J.; Vis, D.J.; Reijmers, T.; Greef, J. van der; Smilde, A.K.; Hendriks, M.M.W.B.

2014-01-01

Modern chromatography-based metabolomics measurements generate large amounts of data in the form of abundances of metabolites. An increasingly popular way of representing and analyzing such data is by means of association networks. Ideally, such a network can be interpreted in terms of the

A Novel Error Resilient Scheme for Wavelet-based Image Coding Over Packet Networks

OpenAIRE

WenZhu Sun; HongYu Wang; DaXing Qian

2012-01-01

this paper presents a robust transmission strategy for wavelet based scalable bit stream over packet erasure channel. By taking the advantage of the bit plane coding and the multiple description coding, the proposed strategy adopts layered multiple description coding (LMDC) for the embedded wavelet coders to improve the error resistant capability of the important bit planes in the meaning of D(R) function. Then, the post-compression rate-distortion (PCRD) optimization process is used to impro...

Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system

International Nuclear Information System (INIS)

Sabahi, Kamel; Teshnehlab, Mohammad; Shoorhedeli, Mahdi Aliyari

2009-01-01

In this study, a new adaptive controller based on modified feedback error learning (FEL) approaches is proposed for load frequency control (LFC) problem. The FEL strategy consists of intelligent and conventional controllers in feedforward and feedback paths, respectively. In this strategy, a conventional feedback controller (CFC), i.e. proportional, integral and derivative (PID) controller, is essential to guarantee global asymptotic stability of the overall system; and an intelligent feedforward controller (INFC) is adopted to learn the inverse of the controlled system. Therefore, when the INFC learns the inverse of controlled system, the tracking of reference signal is done properly. Generally, the CFC is designed at nominal operating conditions of the system and, therefore, fails to provide the best control performance as well as global stability over a wide range of changes in the operating conditions of the system. So, in this study a supervised controller (SC), a lookup table based controller, is addressed for tuning of the CFC. During abrupt changes of the power system parameters, the SC adjusts the PID parameters according to these operating conditions. Moreover, for improving the performance of overall system, a recurrent fuzzy neural network (RFNN) is adopted in INFC instead of the conventional neural network, which was used in past studies. The proposed FEL controller has been compared with the conventional feedback error learning controller (CFEL) and the PID controller through some performance indices

Structural damage detection robust against time synchronization errors

International Nuclear Information System (INIS)

Yan, Guirong; Dyke, Shirley J

2010-01-01

Structural damage detection based on wireless sensor networks can be affected significantly by time synchronization errors among sensors. Precise time synchronization of sensor nodes has been viewed as crucial for addressing this issue. However, precise time synchronization over a long period of time is often impractical in large wireless sensor networks due to two inherent challenges. First, time synchronization needs to be performed periodically, requiring frequent wireless communication among sensors at significant energy cost. Second, significant time synchronization errors may result from node failures which are likely to occur during long-term deployment over civil infrastructures. In this paper, a damage detection approach is proposed that is robust against time synchronization errors in wireless sensor networks. The paper first examines the ways in which time synchronization errors distort identified mode shapes, and then proposes a strategy for reducing distortion in the identified mode shapes. Modified values for these identified mode shapes are then used in conjunction with flexibility-based damage detection methods to localize damage. This alternative approach relaxes the need for frequent sensor synchronization and can tolerate significant time synchronization errors caused by node failures. The proposed approach is successfully demonstrated through numerical simulations and experimental tests in a lab

Mitigation of Voltage Sags in CIGRE Low Voltage Distribution Network

DEFF Research Database (Denmark)

Mustafa, Ghullam; Bak-Jensen, Birgitte; Mahat, Pukar

2013-01-01

Any problem in voltage in a power network is undesirable as it aggravates the quality of the power. Power electronic devices such as Voltage Source Converter (VSC) based Static Synchronous Compensator (STATCOM), Dynamic Voltage Restorer (DVR) etc. are commonly used for the mitigation of voltage p....... The compensation of voltage sags in the different parts of CIGRE distribution network is done by using the four STATCOM compensators already existing in the test grid. The simulations are carried out in DIgSILENT power factory software version 15.0.......Any problem in voltage in a power network is undesirable as it aggravates the quality of the power. Power electronic devices such as Voltage Source Converter (VSC) based Static Synchronous Compensator (STATCOM), Dynamic Voltage Restorer (DVR) etc. are commonly used for the mitigation of voltage...... problems in the distribution system. The voltage problems dealt with in this paper are to show how to mitigate voltage sags in the CIGRE Low Voltage (LV) test network and networks like this. The voltage sags, for the tested cases in the CIGRE LV test network are mainly due to three phase faults...

A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

Directory of Open Access Journals (Sweden)

Linhui Li

2015-01-01

Full Text Available A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Dong Sik Kim

2017-01-01

Full Text Available A low-cost hybrid wireless sensor network (WSN that utilizes the 917 MHz band Wireless Smart Utility Network (Wi-SUN and a 447 MHz band narrow bandwidth communication network is implemented for electric metering and room temperature, humidity, and CO2 gas measurements. A mesh network connection that is commonly utilized for the Internet of Things (IoT is used for the Wi-SUN under the Contiki OS, and a star connection is used for the narrow bandwidth network. Both a duty-cycling receiver algorithm and a digitally controlled temperature-compensated crystal oscillator algorithm for frequency reference are implemented at the physical layer of the receiver to accomplish low-power and low-cost wireless sensor node design. A two-level temperature-compensation approach, in which first a fixed third-order curve and then a sample-based first-order curve are applied, is proposed using a conventional AT-cut quartz crystal resonator. The developed WSN is installed in a home and provides reliable data collection with low construction complexity and power consumption.

Reactive Power Compensating System.

Energy Technology Data Exchange (ETDEWEB)

Williams, Timothy J.; El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.

1985-01-04

The circuit was designed for the specific application of wind-driven induction generators. It has great potential for application in any situation where a varying reactive power load is present, such as with induction motors or generators, or for transmission network compensation.

Synchronization challenges in packet-based Cloud-RAN fronthaul for mobile networks

DEFF Research Database (Denmark)

Checko, Aleksandra; Juul, Anders Christian; Christiansen, Henrik Lehrmann

2015-01-01

In this paper, we look at reusing existing packet-based network (e.g. Ethernet) to possibly decrease deployment costs of fronthaul Cloud Radio Access Network (C-RAN) network and cost of Baseband Unit (BBU) resources. The challenge of this solution is that it requires mobile traffic (until now...... transmitted over synchronous protocols) to traverse the asynchronous Ethernet without losing synchronization. We analyze synchronization requirements of mobile networks and present an overview of solutions that fulfill them in traditional mobile networks. Then we elaborate on challenges that packet-based...... fronthaul imposes. We analyze possible contributions to frequency and phase error. We verify the feasibility of using the IEEE 1588v2 also know as Precision Time Protocol (PTP) for providing accurate phase and frequency synchronization. The study is based on simulations made in OPNET modeler. Thereby we...

Recurrent Neural Network Applications for Astronomical Time Series

Science.gov (United States)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

76 FR 6009 - Shareholder Approval of Executive Compensation and Golden Parachute Compensation

Science.gov (United States)

2011-02-02

.... Consideration of Impact on the Economy, Burden on Competition, and Promotion of Efficiency, Competition, and... Act are available on our Web site at http://www.sec.gov/comments/df-title-ix/executive-compensation...\\ See, e.g., letters from International Corporate Governance Network (``ICGN'') and Teachers Insurance...

Power Flow Calculation for Weakly Meshed Distribution Networks with Multiple DGs Based on Generalized Chain-table Storage Structure

DEFF Research Database (Denmark)

Chen, Shuheng; Hu, Weihao; Chen, Zhe

2014-01-01

Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target is to de......Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target...... is to describe the topology of radial distribution networks with a clear logic and a small memory size. The strategies of compensating the equivalent currents of break-point branches and the reactive power outputs of PV-type DGs are presented on the basis of superposition theorem. Their formulations...... are simplified to be the final multi-variable linear functions. Furthermore, an accelerating factor is applied to the outer-layer reactive power compensation for improving the convergence procedure. Finally, the proposed power flow method is performed in program language VC++ 6.0, and numerical tests have been...

Refraction-compensated motion tracking of unrestrained small animals in positron emission tomography.

Science.gov (United States)

Kyme, Andre; Meikle, Steven; Baldock, Clive; Fulton, Roger

2012-08-01

Motion-compensated radiotracer imaging of fully conscious rodents represents an important paradigm shift for preclinical investigations. In such studies, if motion tracking is performed through a transparent enclosure containing the awake animal, light refraction at the interface will introduce errors in stereo pose estimation. We have performed a thorough investigation of how this impacts the accuracy of pose estimates and the resulting motion correction, and developed an efficient method to predict and correct for refraction-based error. The refraction model underlying this study was validated using a state-of-the-art motion tracking system. Refraction-based error was shown to be dependent on tracking marker size, working distance, and interface thickness and tilt. Correcting for refraction error improved the spatial resolution and quantitative accuracy of motion-corrected positron emission tomography images. Since the methods are general, they may also be useful in other contexts where data are corrupted by refraction effects. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Sagnac secret sharing over telecom fiber networks.

Science.gov (United States)

Bogdanski, Jan; Ahrens, Johan; Bourennane, Mohamed

2009-01-19

We report the first Sagnac quantum secret sharing (in three-and four-party implementations) over 1550 nm single mode fiber (SMF) networks, using a single qubit protocol with phase encoding. Our secret sharing experiment has been based on a single qubit protocol, which has opened the door to practical secret sharing implementation over fiber telecom channels and in free-space. The previous quantum secret sharing proposals were based on multiparticle entangled states, difficult in the practical implementation and not scalable. Our experimental data in the three-party implementation show stable (in regards to birefringence drift) quantum secret sharing transmissions at the total Sagnac transmission loop distances of 55-75 km with the quantum bit error rates (QBER) of 2.3-2.4% for the mean photon number micro?= 0.1 and 1.7-2.1% for micro= 0.3. In the four-party case we have achieved quantum secret sharing transmissions at the total Sagnac transmission loop distances of 45-55 km with the quantum bit error rates (QBER) of 3.0-3.7% for the mean photon number micro= 0.1 and 1.8-3.0% for micro?= 0.3. The stability of quantum transmission has been achieved thanks to our new concept for compensation of SMF birefringence effects in Sagnac, based on a polarization control system and a polarization insensitive phase modulator. The measurement results have showed feasibility of quantum secret sharing over telecom fiber networks in Sagnac configuration, using standard fiber telecom components.

Assessment of Motor Control during Three-Dimensional Movements Tracking with Position-Varying Gravity Compensation

Directory of Open Access Journals (Sweden)

Yao Huang

2017-05-01

Full Text Available Active movements are important in the rehabilitation training for patients with neurological motor disorders, while weight of upper limb impedes movements due to muscles weakness. The objective of this study is to develop a position-varying gravity compensation strategy for a cable-based rehabilitation robot. The control strategy can estimate real-time gravity torque according to position feedback. Then, the performance of this control strategy was compared with the other two kinds of gravity compensation strategies (i.e., without compensation and with fixed compensation during movements tracking. Seven healthy subjects were invited to conduct tracking tasks along four different directions (i.e., upward, forward, leftward, and rightward. The performance of movements with different compensation strategies was compared in terms of root mean square error (RMSE between target and actual moving trajectories, normalized jerk score (NJS, mean velocity ratio (MVR of main motion direction, and the activation of six muscles. The results showed that there were significant effects in control strategies in all four directions with the RMSE and NJS values in the following order: without compensation > fixed compensation > position-varying compensation and MVR values in the following order: without compensation < fixed compensation < position-varying compensation (p < 0.05. Comparing with movements without compensation in all four directions, the activation of muscles during movements with position-varying compensation showed significant reductions, except the activations of triceps and in forward and leftward movements, the activations of upper trapezius and middle parts of deltoid in upward movements and the activations of posterior parts of deltoid in all four directions (p < 0.05. Therefore, with position-varying gravity compensation, the upper limb cable-based rehabilitation robotic system might assist subjects to perform movements with higher quality and

What is different about workers' compensation patients? Socioeconomic predictors of baseline disability status among patients with lumbar radiculopathy.

Science.gov (United States)

Atlas, Steven J; Tosteson, Tor D; Hanscom, Brett; Blood, Emily A; Pransky, Glenn S; Abdu, William A; Andersson, Gunnar B; Weinstein, James N

2007-08-15

Combined analysis of 2 prospective clinical studies. To identify socioeconomic characteristics associated with workers' compensation in patients with an intervertebral disc herniation (IDH) or spinal stenosis (SpS). Few studies have compared socioeconomic differences between those receiving or not receiving workers' compensation with the same underlying clinical conditions. Patients were identified from the Spine Patient Outcomes Research Trial (SPORT) and the National Spine Network (NSN) practice-based outcomes study. Patients with IDH and SpS within NSN were identified satisfying SPORT eligibility criteria. Information on disability and work status at baseline evaluation was used to categorize patients into 3 groups: workers' compensation, other disability compensation, or work-eligible controls. Enrollment rates of patients with disability in a clinical efficacy trial (SPORT) and practice-based network (NSN) were compared. Independent socioeconomic predictors of baseline workers' compensation status were identified in multivariate logistic regression models controlling for clinical condition, study cohort, and initial treatment designation. Among 3759 eligible patients (1480 in SPORT and 2279 in NSN), 564 (15%) were receiving workers' compensation, 317 (8%) were receiving other disability compensation, and 2878 (77%) were controls. Patients receiving workers' compensation were less common in SPORT than NSN (9.2% vs. 18.8%, P socioeconomic characteristics significantly differed according to baseline workers' compensation status. In multiple logistic regression analyses, gender, educational level, work characteristics, legal action, and expectations about ability to work without surgery were independently associated with receiving workers' compensation. Clinical trials involving conditions commonly seen in patients with workers' compensation may need special efforts to ensure adequate representation. Socioeconomic characteristics markedly differed between patients

Introduction to precision machine design and error assessment

CERN Document Server

Mekid, Samir

2008-01-01

While ultra-precision machines are now achieving sub-nanometer accuracy, unique challenges continue to arise due to their tight specifications. Written to meet the growing needs of mechanical engineers and other professionals to understand these specialized design process issues, Introduction to Precision Machine Design and Error Assessment places a particular focus on the errors associated with precision design, machine diagnostics, error modeling, and error compensation. Error Assessment and ControlThe book begins with a brief overview of precision engineering and applications before introdu

Person-based differences in pay reactions: A compensation-activation theory and integrative conceptual review.

Science.gov (United States)

Fulmer, Ingrid Smithey; Shaw, Jason D

2018-06-07

Compensation research has focused traditionally on how pay design characteristics (e.g., pay level, individual or group incentives) relate to average employee outcomes and, in toto, on how these outcomes affect organizational performance. Recently, scholars have begun to pay more attention to how individuals vary in the strength of their reactions to pay. Empirical research in several disciplines examines how the interplay of pay systems and person-based characteristics (psychological individual differences, demographics, and relative performance or position in a group) relate to important work-related outcomes. We develop a compensation-activation theory that frames compensation design characteristics as workplace "situations" providing cues that activate individuals' corresponding fundamental social motives made salient due to chronic or transient person-based characteristics. Where activation occurs, stronger-than-average responses to the compensation "situation" are expected. Using the theory as a lens, we synthesize and reinterpret existing research on person-based reactions to pay characteristics, including sorting, incentive/motivational effects, and effects on collective pay system reactions and unit/organizational outcomes. We conclude with a research agenda aimed at refining compensation-activation theory and advancing the study of compensation as it affects individual and organizational outcomes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Inertia compensated force and pressure sensors

Energy Technology Data Exchange (ETDEWEB)

Bill, B.; Engeler, P.; Gossweiler, C. [Kistler Instrumente AG, Winterthur (Switzerland)

2001-07-01

Any moving structure is affected by inertial effects. In case of force and pressure sensors, inertial effects cause measurement errors. The paper deals with novel signal conditioning methods and mechanical design features to minimize inertial effects. A novel solution for passive compensation of pressure sensors is presented. (orig.)

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

Science.gov (United States)

Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

Measurement system and model for simultaneously measuring 6DOF geometric errors.

Science.gov (United States)

Zhao, Yuqiong; Zhang, Bin; Feng, Qibo

2017-09-04

A measurement system to simultaneously measure six degree-of-freedom (6DOF) geometric errors is proposed. The measurement method is based on a combination of mono-frequency laser interferometry and laser fiber collimation. A simpler and more integrated optical configuration is designed. To compensate for the measurement errors introduced by error crosstalk, element fabrication error, laser beam drift, and nonparallelism of two measurement beam, a unified measurement model, which can improve the measurement accuracy, is deduced and established using the ray-tracing method. A numerical simulation using the optical design software Zemax is conducted, and the results verify the correctness of the model. Several experiments are performed to demonstrate the feasibility and effectiveness of the proposed system and measurement model.

Reliability improvement for anisotropic biased compensated α/β contamination meter

Energy Technology Data Exchange (ETDEWEB)

Coulon, R., E-mail: romain.coulon@cea.fr [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Montagu, T. [CEA, LIST, Laboratoire de Modélisation et Simulation des Systèmes, F-91191 Gif-sur-Yvette (France); Schoepff, V. [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Menaa, N.; Ulmann, A. Gallozzi; Blanc de Lanaute, N. [CANBERRA France, F-78182 St Quentin en Yvelines (France)

2016-11-21

Nuclear instruments such as alpha/beta contamination meter are frequently used in a compensated mode where the contribution of gamma radiation background is compensated by a guard detector. The signal of interest is then the subtraction of counting from both channels. In practice, the noise signal measured by the guard detector is not strictly equal to the noise contribution into the first detector due to anisotropic biases. The random error (under Poisson assumption) is taken into account to build a hypothesis test. The system is also designed to minimize the systematic error but in some cases, this bias could not be completely removed. The measurement system then shows different behavior when the surrounding environment changes exhibiting inopportune false alarms. A method allowing the false alarms to be suppressed is addressed in this study for compensated measurement. An improvement in terms of reliability has been proven.

A Model of Gravity Vector Measurement Noise for Estimating Accelerometer Bias in Gravity Disturbance Compensation.

Science.gov (United States)

Tie, Junbo; Cao, Juliang; Chang, Lubing; Cai, Shaokun; Wu, Meiping; Lian, Junxiang

2018-03-16

Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method.

A Model of Gravity Vector Measurement Noise for Estimating Accelerometer Bias in Gravity Disturbance Compensation

Science.gov (United States)

Cao, Juliang; Cai, Shaokun; Wu, Meiping; Lian, Junxiang

2018-01-01

Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method. PMID:29547552

Rain Fade Compensation for Ka-Band Communications Satellites

Science.gov (United States)

Mitchell, W. Carl; Nguyen, Lan; Dissanayake, Asoka; Markey, Brian; Le, Anh

1997-01-01

This report provides a review and evaluation of rain fade measurement and compensation techniques for Ka-band satellite systems. This report includes a description of and cost estimates for performing three rain fade measurement and compensation experiments. The first experiment deals with rain fade measurement techniques while the second one covers the rain fade compensation techniques. The third experiment addresses a feedback flow control technique for the ABR service (for ATM-based traffic). The following conclusions were observed in this report; a sufficient system signal margin should be allocated for all carriers in a network, that is a fixed clear-sky margin should be typically in the range of 4-5 dB and should be more like 15 dB in the up link for moderate and heavy rain zones; to obtain a higher system margin it is desirable to combine the uplink power control technique with the technique that implements the source information rate and FEC code rate changes resulting in a 4-5 dB increase in the dynamic part of the system margin. The experiments would assess the feasibility of the fade measurements and compensation techniques, and ABR feedback control technique.

Control of GMA Butt Joint Welding Based on Neural Networks

DEFF Research Database (Denmark)

Christensen, Kim Hardam; Sørensen, Torben

2004-01-01

This paper presents results from an experimentally based research on Gas Metal Arc Welding (GMAW), controlled by the artificial neural network (ANN) technology. A system has been developed for modeling and online adjustment of welding parameters, appropriate to guarantee a high degree of quality......-linear least square error minimization, has been used with the back-propagation algorithm for training the network, while a Bayesian regularization technique has been successfully applied for minimizing the risk of inexpedient over-training....

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

Science.gov (United States)

Peng, Zhouhua; Wang, Dan; Wang, Wei; Liu, Lu

2015-11-01

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Error Control Techniques for Efficient Multicast Streaming in UMTS Networks: Proposals andPerformance Evaluation

Directory of Open Access Journals (Sweden)

Michele Rossi

2004-06-01

Full Text Available In this paper we introduce techniques for efficient multicast video streaming in UMTS networks where a video content has to be conveyed to multiple users in the same cell. Efficient multicast data delivery in UMTS is still an open issue. In particular, suitable solutions have to be found to cope with wireless channel errors, while maintaining both an acceptable channel utilization and a controlled delivery delay over the wireless link between the serving base station and the mobile terminals. Here, we first highlight that standard solutions such as unequal error protection (UEP of the video flow are ineffective in the UMTS systems due to its inherent large feedback delay at the link layer (Radio Link Control, RLC. Subsequently, we propose a local approach to solve errors directly at the UMTS link layer while keeping a reasonably high channel efficiency and saving, as much as possible, system resources. The solution that we propose in this paper is based on the usage of the common channel to serve all the interested users in a cell. In this way, we can save resources with respect to the case where multiple dedicated channels are allocated for every user. In addition to that, we present a hybrid ARQ (HARQ proactive protocol that, at the cost of some redundancy (added to the link layer flow, is able to consistently improve the channel efficiency with respect to the plain ARQ case, by therefore making the use of a single common channel for multicast data delivery feasible. In the last part of the paper we give some hints for future research, by envisioning the usage of the aforementioned error control protocols with suitably encoded video streams.

Reliability estimation of safety-critical software-based systems using Bayesian networks

International Nuclear Information System (INIS)

Helminen, A.

2001-06-01

Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of software-based safety-critical automation systems in nuclear power plants. In the research project 'Programmable automation system safety integrity assessment (PASSI)', belonging to the Finnish Nuclear Safety Research Programme (FINNUS, 1999-2002), various safety assessment methods and tools for software based systems are developed and evaluated. The project is financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT). In this report the applicability of Bayesian networks to the reliability estimation of software-based systems is studied. The applicability is evaluated by building Bayesian network models for the systems of interest and performing simulations for these models. In the simulations hypothetical evidence is used for defining the parameter relations and for determining the ability to compensate disparate evidence in the models. Based on the experiences from modelling and simulations we are able to conclude that Bayesian networks provide a good method for the reliability estimation of software-based systems. (orig.)

Resolution dependence on phase extraction by the Hilbert transform in phase calibrated and dispersion compensated ultrahigh resolution spectrometer-based OCT

DEFF Research Database (Denmark)

Israelsen, Niels Møller; Maria, Michael; Feuchter, Thomas

2018-01-01

-linearities lead together to an unknown chirp of the detected interferogram. One method to compensate for the chirp is to perform a pixel-wavenumber calibration versus phase that requires numerical extraction of the phase. Typically a Hilbert transform algorithm is employed to extract the optical phase versus...... wavenumber for calibration and dispersion compensation. In this work we demonstrate UHR-OCT at 1300 nm using a Super continuum source and highlight the resolution constraints in using the Hilbert transform algorithm when extracting the optical phase for calibration and dispersion compensation. We demonstrate...... that the constraints cannot be explained purely by the numerical errors in the data processing module utilizing the Hilbert transform but must be dictated by broadening mechanisms originating from the experimentally obtained interferograms....

The Quota-Based Compensation Plan in Fashion Retailing Industry under Asymmetric Information

Directory of Open Access Journals (Sweden)

Mingzhu Yu

2014-01-01

Full Text Available We study a compensation plan problem in the fashion retailing industry, which involves a risk-neutral fashion retailer and a risk-neutral salesperson, in a two-stage game framework with asymmetric information. In the first stage, the fashion retailer provides a menu of compensation plans to the salesperson who decides which plan to sign based on his superior market demand information. Confronted with the asymmetric demand information, the fashion retailer could observe market information from the salesperson's response by designing a menu of compensation plans rather than a single one to the salesperson. In the second stage, the fashion retailer then makes production decision and the salesperson determines his selling effort. We consider both adverse selection and moral hazard. We adopt the quota-based plan to derive the fashion retailer’s optimal compensation plan design and the salesperson's best response. We emphasize the impact of the quota level on the system outcomes. The results reveal that a higher quota level is disadvantageous to the fashion retailer but advantageous to the salespersons.

Creative compensation

International Nuclear Information System (INIS)

Coll, D.

1994-01-01

A discussion is presented of executive compensation in Canada's petroleum industry. Mandatory disclosure of executive compensation and benefits is regulated by the Ontario Securities Commission. Examination of the compensation packages of 80 oilpatch CEOs shows a clear difference in philosophy between large and small companies. Larger companies pay larger salaries, offer pension plans, and reward long-term loyalty. Within smaller companies, compensation tends to be linked with stock performance. Trends in compensation are to lower base salaries with more variables such as bonuses, cash incentives and gain-sharing programs. Increasing shareholder scrutiny is prompting more stringent guidelines on stock option plans. Some companies place performance conditions on stock vesting. Another option is to grant premium priced options to executives, to increase the gains required for the executive to post a profit. Other comapanies are granting stock options to their field personnel, or are granting stock to all employees. Directors are playing an increasing role in executive compensation. 4 tabs

Creative compensation

Energy Technology Data Exchange (ETDEWEB)

Coll, D

1994-09-19

A discussion is presented of executive compensation in Canada's petroleum industry. Mandatory disclosure of executive compensation and benefits is regulated by the Ontario Securities Commission. Examination of the compensation packages of 80 oilpatch CEOs shows a clear difference in philosophy between large and small companies. Larger companies pay larger salaries, offer pension plans, and reward long-term loyalty. Within smaller companies, compensation tends to be linked with stock performance. Trends in compensation are to lower base salaries with more variables such as bonuses, cash incentives and gain-sharing programs. Increasing shareholder scrutiny is prompting more stringent guidelines on stock option plans. Some companies place performance conditions on stock vesting. Another option is to grant premium priced options to executives, to increase the gains required for the executive to post a profit. Other comapanies are granting stock options to their field personnel, or are granting stock to all employees. Directors are playing an increasing role in executive compensation. 4 tabs.

Image-based motion compensation for high-resolution extremities cone-beam CT

Science.gov (United States)

Sisniega, A.; Stayman, J. W.; Cao, Q.; Yorkston, J.; Siewerdsen, J. H.; Zbijewski, W.

2016-03-01

Purpose: Cone-beam CT (CBCT) of the extremities provides high spatial resolution, but its quantitative accuracy may be challenged by involuntary sub-mm patient motion that cannot be eliminated with simple means of external immobilization. We investigate a two-step iterative motion compensation based on a multi-component metric of image sharpness. Methods: Motion is considered with respect to locally rigid motion within a particular region of interest, and the method supports application to multiple locally rigid regions. Motion is estimated by maximizing a cost function with three components: a gradient metric encouraging image sharpness, an entropy term that favors high contrast and penalizes streaks, and a penalty term encouraging smooth motion. Motion compensation involved initial coarse estimation of gross motion followed by estimation of fine-scale displacements using high resolution reconstructions. The method was evaluated in simulations with synthetic motion (1-4 mm) applied to a wrist volume obtained on a CMOS-based CBCT testbench. Structural similarity index (SSIM) quantified the agreement between motion-compensated and static data. The algorithm was also tested on a motion contaminated patient scan from dedicated extremities CBCT. Results: Excellent correction was achieved for the investigated range of displacements, indicated by good visual agreement with the static data. 10-15% improvement in SSIM was attained for 2-4 mm motions. The compensation was robust against increasing motion (4% decrease in SSIM across the investigated range, compared to 14% with no compensation). Consistent performance was achieved across a range of noise levels. Significant mitigation of artifacts was shown in patient data. Conclusion: The results indicate feasibility of image-based motion correction in extremities CBCT without the need for a priori motion models, external trackers, or fiducials.

A flexible and cost-effective compensation method for leveling using large-scale coordinate measuring machines and its application in aircraft digital assembly

Science.gov (United States)

Deng, Zhengping; Li, Shuanggao; Huang, Xiang

2018-06-01

In the assembly process of large-size aerospace products, the leveling and horizontal alignment of large components are essential prior to the installation of an inertial navigation system (INS) and the final quality inspection. In general, the inherent coordinate systems of large-scale coordinate measuring devices are not coincident with the geodetic horizontal system, and a dual-axis compensation system is commonly required for the measurement of difference in heights. These compensation systems are expensive and dedicated designs for different devices at present. Considering that a large-size assembly site usually needs more than one measuring device, a compensation approach which is versatile for different devices would be a more convenient and economic choice for manufacturers. In this paper, a flexible and cost-effective compensation method is proposed. Firstly, an auxiliary measuring device called a versatile compensation fixture (VCF) is designed, which mainly comprises reference points for coordinate transformation and a dual-axis inclinometer, and a kind of network tighten points (NTPs) are introduced and temporarily deployed in the large measuring space to further reduce transformation error. Secondly, the measuring principle of height difference is studied, based on coordinate transformation theory and trigonometry while considering the effects of earth curvature, and the coordinate transformation parameters are derived by least squares adjustment. Thirdly, the analytical solution of leveling uncertainty is analyzed, based on which the key parameters of the VCF and the proper deployment of NTPs are determined according to the leveling accuracy requirement. Furthermore, the proposed method is practically applied to the assembly of a large helicopter by developing an automatic leveling and alignment system. By measuring four NTPs, the leveling uncertainty (2σ) is reduced by 29.4% to about 0.12 mm, compared with that without NTPs.

Compensation for gravitational sag of bent mirror

Energy Technology Data Exchange (ETDEWEB)

Mao, Chengwen; Jiang, Hui; He, Yan; Liang, Dongxu; Lan, Xuying; Yan, Shuai [Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, CAS, Shanghai 201800 (China); Shu, De-ming [Advanced Photon Source, Argonne National Laboratory, Argonne, IL 60439 (United States); Li, Aiguo, E-mail: aiguo.li@sinap.ac.cn [Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics, CAS, Shanghai 201800 (China)

2017-05-01

The gravitational sag of aspheric bent mirrors with face-up or face-down geometry produces a nonnegligible optical error. As an effective compensation, width optimization is used to match the combined effects of the gravitational and bending moments. This method is described by analytical expressions and two calculation algorithms. The results of theoretical simulations and finite element analysis have proved that this method can reduce the slope error resulting from gravitational sag to the level of nano radians.

Compensation for gravitational sag of bent mirror

International Nuclear Information System (INIS)

Mao, Chengwen; Jiang, Hui; He, Yan; Liang, Dongxu; Lan, Xuying; Yan, Shuai; Shu, De-ming; Li, Aiguo

2017-01-01

The gravitational sag of aspheric bent mirrors with face-up or face-down geometry produces a nonnegligible optical error. As an effective compensation, width optimization is used to match the combined effects of the gravitational and bending moments. This method is described by analytical expressions and two calculation algorithms. The results of theoretical simulations and finite element analysis have proved that this method can reduce the slope error resulting from gravitational sag to the level of nano radians.

TH-EF-BRB-08: Robotic Motion Compensation for Radiation Therapy: A 6DOF Phantom Study

Energy Technology Data Exchange (ETDEWEB)

Belcher, AH; Liu, X; Wiersma, R [The University of Chicago, Chicago, IL (United States)

2016-06-15

Purpose: The high accuracy of frame-based stereotactic radiosurgery (SRS), which uses a rigid frame fixed to the patient’s skull, is offset by potential drawbacks of poor patient compliance and clinical workflow restrictions. Recent research into frameless SRS has so far resulted in reduced accuracy. In this study, we investigate the use of a novel 6 degree-of-freedom (6DOF) robotic head motion cancellation system that continuously detects and compensates for patient head motions during a SRS delivery. This approach has the potential to reduce invasiveness while still achieving accuracies better or equal to traditional frame-based SRS. Methods: A 6DOF parallel kinematics robotics stage was constructed, and controlled using an inverse kinematics-based motion compensation algorithm. A 6DOF stereoscopic infrared (IR) marker tracking system was used to monitor real-time motions at sub-millimeter and sub-degree levels. A novel 6DOF calibration technique was first applied to properly orient the camera coordinate frame to match that of the LINAC and robotic control frames. Simulated head motions were measured by the system, and the robotic stage responded to these 6DOF motions automatically, returning the reflective marker coordinate frame to its original position. Results: After the motions were introduced to the system in the phantom-based study, the robotic stage automatically and rapidly returned the phantom to LINAC isocenter. When errors exceeded the compensation lower threshold of 0.25 mm or 0.25 degrees, the system registered the 6DOF error and generated a cancellation trajectory. The system responded in less than 0.5 seconds and returned all axes to less than 0.1 mm and 0.1 degree after the 6DOF compensation was performed. Conclusion: The 6DOF real-time motion cancellation system was found to be effective at compensating for translational and rotational motions to current SRS requirements. This system can improve frameless SRS by automatically returning

TH-EF-BRB-08: Robotic Motion Compensation for Radiation Therapy: A 6DOF Phantom Study

International Nuclear Information System (INIS)

Belcher, AH; Liu, X; Wiersma, R

2016-01-01

Purpose: The high accuracy of frame-based stereotactic radiosurgery (SRS), which uses a rigid frame fixed to the patient’s skull, is offset by potential drawbacks of poor patient compliance and clinical workflow restrictions. Recent research into frameless SRS has so far resulted in reduced accuracy. In this study, we investigate the use of a novel 6 degree-of-freedom (6DOF) robotic head motion cancellation system that continuously detects and compensates for patient head motions during a SRS delivery. This approach has the potential to reduce invasiveness while still achieving accuracies better or equal to traditional frame-based SRS. Methods: A 6DOF parallel kinematics robotics stage was constructed, and controlled using an inverse kinematics-based motion compensation algorithm. A 6DOF stereoscopic infrared (IR) marker tracking system was used to monitor real-time motions at sub-millimeter and sub-degree levels. A novel 6DOF calibration technique was first applied to properly orient the camera coordinate frame to match that of the LINAC and robotic control frames. Simulated head motions were measured by the system, and the robotic stage responded to these 6DOF motions automatically, returning the reflective marker coordinate frame to its original position. Results: After the motions were introduced to the system in the phantom-based study, the robotic stage automatically and rapidly returned the phantom to LINAC isocenter. When errors exceeded the compensation lower threshold of 0.25 mm or 0.25 degrees, the system registered the 6DOF error and generated a cancellation trajectory. The system responded in less than 0.5 seconds and returned all axes to less than 0.1 mm and 0.1 degree after the 6DOF compensation was performed. Conclusion: The 6DOF real-time motion cancellation system was found to be effective at compensating for translational and rotational motions to current SRS requirements. This system can improve frameless SRS by automatically returning

A holistic calibration method with iterative distortion compensation for stereo deflectometry

Science.gov (United States)

Xu, Yongjia; Gao, Feng; Zhang, Zonghua; Jiang, Xiangqian

2018-07-01

This paper presents a novel holistic calibration method for stereo deflectometry system to improve the system measurement accuracy. The reconstruction result of stereo deflectometry is integrated with the calculated normal data of the measured surface. The calculation accuracy of the normal data is seriously influenced by the calibration accuracy of the geometrical relationship of the stereo deflectometry system. Conventional calibration approaches introduce form error to the system due to inaccurate imaging model and distortion elimination. The proposed calibration method compensates system distortion based on an iterative algorithm instead of the conventional distortion mathematical model. The initial value of the system parameters are calculated from the fringe patterns displayed on the systemic LCD screen through a reflection of a markless flat mirror. An iterative algorithm is proposed to compensate system distortion and optimize camera imaging parameters and system geometrical relation parameters based on a cost function. Both simulation work and experimental results show the proposed calibration method can significantly improve the calibration and measurement accuracy of a stereo deflectometry. The PV (peak value) of measurement error of a flat mirror can be reduced to 69.7 nm by applying the proposed method from 282 nm obtained with the conventional calibration approach.

Optimal coordination of distance and over-current relays in series compensated systems based on MAPSO

International Nuclear Information System (INIS)

Moravej, Zahra; Jazaeri, Mostafa; Gholamzadeh, Mehdi

2012-01-01

Highlight: ► Optimal coordination problem between distance relays and Directional Over-Current Relays (DOCRs) is studied. ► A new problem formulation for both uncompensated and series compensated system is proposed. ► In order to solve the coordination problem a Modified Adaptive Particle Swarm Optimization (MAPSO) is employed. ► The optimum results are found in both uncompensated and series compensated systems. - Abstract: In this paper, a novel problem formulation for optimal coordination between distance relays and Directional Over-Current Relays (DOCRs) in series compensated systems is proposed. The integration of the series capacitor (SC) into the transmission line makes the coordination problem more complex. The main contribution of this paper is a new systematic method for computing the optimal second zone timing of distance relays and optimal settings of DOCRs, in series compensated and uncompensated transmission systems, which have a combined protection scheme with DOCRs and distance relays. In order to solve this coordination problem, which is a nonlinear and non-convex problem, a Modified Adaptive Particle Swarm Optimization (MAPSO) is employed. The new proposed method is supported by obtained results from a typical test case and a real power system network.

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

Science.gov (United States)

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Feedforward compensation for novel dynamics depends on force field orientation but is similar for the left and right arms.

Science.gov (United States)

Reuter, Eva-Maria; Cunnington, Ross; Mattingley, Jason B; Riek, Stephan; Carroll, Timothy J

2016-11-01

There are well-documented differences in the way that people typically perform identical motor tasks with their dominant and the nondominant arms. According to Yadav and Sainburg's (Neuroscience 196: 153-167, 2011) hybrid-control model, this is because the two arms rely to different degrees on impedance control versus predictive control processes. Here, we assessed whether differences in limb control mechanisms influence the rate of feedforward compensation to a novel dynamic environment. Seventy-five healthy, right-handed participants, divided into four subsamples depending on the arm (left, right) and direction of the force field (ipsilateral, contralateral), reached to central targets in velocity-dependent curl force fields. We assessed the rate at which participants developed predictive compensation for the force field using intermittent error-clamp trials and assessed both kinematic errors and initial aiming angles in the field trials. Participants who were exposed to fields that pushed the limb toward ipsilateral space reduced kinematic errors more slowly, built up less predictive field compensation, and relied more on strategic reaiming than those exposed to contralateral fields. However, there were no significant differences in predictive field compensation or kinematic errors between limbs, suggesting that participants using either the left or the right arm could adapt equally well to novel dynamics. It therefore appears that the distinct preferences in control mechanisms typically observed for the dominant and nondominant arms reflect a default mode that is based on habitual functional requirements rather than an absolute limit in capacity to access the controller specialized for the opposite limb. Copyright © 2016 the American Physiological Society.

Residual translation compensations in radar target narrowband imaging based on trajectory information

Science.gov (United States)

Yue, Wenjue; Peng, Bo; Wei, Xizhang; Li, Xiang; Liao, Dongping

2018-05-01

High velocity translation will result in defocusing scattering centers in radar imaging. In this paper, we propose a Residual Translation Compensations (RTC) method based on target trajectory information to eliminate the translation effects in radar imaging. Translation could not be simply regarded as a uniformly accelerated motion in reality. So the prior knowledge of the target trajectory is introduced to enhance compensation precision. First we use the two-body orbit model to figure out the radial distance. Then, stepwise compensations are applied to eliminate residual propagation delay based on conjugate multiplication method. Finally, tomography is used to confirm the validity of the method. Compare with translation parameters estimation method based on the spectral peak of the conjugate multiplied signal, RTC method in this paper enjoys a better tomography result. When the Signal Noise Ratio (SNR) of the radar echo signal is 4dB, the scattering centers can also be extracted clearly.

Motion-compensated optical coherence tomography using envelope-based surface detection and Kalman-based prediction

Science.gov (United States)

Irsch, Kristina; Lee, Soohyun; Bose, Sanjukta N.; Kang, Jin U.

2018-02-01

We present an optical coherence tomography (OCT) imaging system that effectively compensates unwanted axial motion with micron-scale accuracy. The OCT system is based on a swept-source (SS) engine (1060-nm center wavelength, 100-nm full-width sweeping bandwidth, and 100-kHz repetition rate), with axial and lateral resolutions of about 4.5 and 8.5 microns respectively. The SS-OCT system incorporates a distance sensing method utilizing an envelope-based surface detection algorithm. The algorithm locates the target surface from the B-scans, taking into account not just the first or highest peak but the entire signature of sequential A-scans. Subsequently, a Kalman filter is applied as predictor to make up for system latencies, before sending the calculated position information to control a linear motor, adjusting and maintaining a fixed system-target distance. To test system performance, the motioncorrection algorithm was compared to earlier, more basic peak-based surface detection methods and to performing no motion compensation. Results demonstrate increased robustness and reproducibility, particularly noticeable in multilayered tissues, while utilizing the novel technique. Implementing such motion compensation into clinical OCT systems may thus improve the reliability of objective and quantitative information that can be extracted from OCT measurements.

Optimal compensation for neuron loss

Science.gov (United States)

Barrett, David GT; Denève, Sophie; Machens, Christian K

2016-01-01

The brain has an impressive ability to withstand neural damage. Diseases that kill neurons can go unnoticed for years, and incomplete brain lesions or silencing of neurons often fail to produce any behavioral effect. How does the brain compensate for such damage, and what are the limits of this compensation? We propose that neural circuits instantly compensate for neuron loss, thereby preserving their function as much as possible. We show that this compensation can explain changes in tuning curves induced by neuron silencing across a variety of systems, including the primary visual cortex. We find that compensatory mechanisms can be implemented through the dynamics of networks with a tight balance of excitation and inhibition, without requiring synaptic plasticity. The limits of this compensatory mechanism are reached when excitation and inhibition become unbalanced, thereby demarcating a recovery boundary, where signal representation fails and where diseases may become symptomatic. DOI: http://dx.doi.org/10.7554/eLife.12454.001 PMID:27935480

Systematic Errors in Dimensional X-ray Computed Tomography

DEFF Research Database (Denmark)

that it is possible to compensate them. In dimensional X-ray computed tomography (CT), many physical quantities influence the final result. However, it is important to know which factors in CT measurements potentially lead to systematic errors. In this talk, typical error sources in dimensional X-ray CT are discussed...

Refractive optics to compensate x-ray mirror shape-errors

Science.gov (United States)

Laundy, David; Sawhney, Kawal; Dhamgaye, Vishal; Pape, Ian

2017-08-01

Elliptically profiled mirrors operating at glancing angle are frequently used at X-ray synchrotron sources to focus X-rays into sub-micrometer sized spots. Mirror figure error, defined as the height difference function between the actual mirror surface and the ideal elliptical profile, causes a perturbation of the X-ray wavefront for X- rays reflecting from the mirror. This perturbation, when propagated to the focal plane results in an increase in the size of the focused beam. At Diamond Light Source we are developing refractive optics that can be used to locally cancel out the wavefront distortion caused by figure error from nano-focusing elliptical mirrors. These optics could be used to correct existing optical components on synchrotron radiation beamlines in order to give focused X-ray beam sizes approaching the theoretical diffraction limit. We present our latest results showing measurement of the X-ray wavefront error after reflection from X-ray mirrors and the translation of the measured wavefront into a design for refractive optical elements for correction of the X-ray wavefront. We show measurement of the focused beam with and without the corrective optics inserted showing reduction in the size of the focus resulting from the correction to the wavefront.

Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

Science.gov (United States)

Hwang, Chih-Lyang; Jan, Chau

2016-02-01

At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

Non-binary unitary error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E.

1996-06-01

Error operator bases for systems of any dimension are defined and natural generalizations of the bit-flip/ sign-change error basis for qubits are given. These bases allow generalizing the construction of quantum codes based on eigenspaces of Abelian groups. As a consequence, quantum codes can be constructed form linear codes over {ital Z}{sub {ital n}} for any {ital n}. The generalization of the punctured code construction leads to many codes which permit transversal (i.e. fault tolerant) implementations of certain operations compatible with the error basis.