Electrohydraulic proportional position and pressure loading control utilizing a state perception and processing method.

A new multifunctional proportional control triaxial stress loading apparatus is presented in this study, which can apply an output force on coal rock to simulate the conditions of triaxial stress loading, aiming at solving the problems of excessive consideration of static indices in the design and the incompleteness of the simulation and test verification system for the test parts at the performance analysis stage. This apparatus mainly combines the configuration of a triaxial stress loading system which can meet the stress loading requirements under different operating conditions, with the effective integration of multiple pressure loading operations based on the electrohydraulic proportional control method. In this context, a pressure and position combined control strategy based on the sliding mode is proposed to control the vertical and longitudinal loading hydraulic cylinders. Then, a co-simulation mode including the triaxial stress loading hydraulic system is established to verify the control strategy, system response characteristics and selection of the controller parameters. Furthermore, a multifunctional stress loading experimental platform is developed, and the stress loading characteristics with the proposed strategy are tested and analyzed. The results show that the triaxial stress loading hydraulic system can meet the response characteristics, the fluctuating deviation of the constant loading test can be restricted to 8.5%, the tracking error of the variable loading test is small, the minimum response time of instantaneous loading can reach 2.8 s, and the stress loading effect is noticeable. The experimental platform fully indicates that the stress loading system with the state perception and processing method as the core can meet a variety of verification indices of constant, variable and instantaneous loading tests. This research provides technical support for the smooth, synchronous control and intelligent operation of various types of hydraulic actuator machines.

Comparison of dynamic tumor tracking error measurement methods for robotic radiosurgery.

BACKGROUND: Dynamic tumor motion tracking is used in robotic radiosurgery for targets subject to respiratory motion, such as lung and liver cancers. Different methods of measuring tracking error have been reported, but the differences among these methods have not been studied, and the optimal method is unknown. PURPOSE: The purpose of this study was to assess and compare tracking errors encountered with individual patients using different evaluation methods for method optimization. METHODS: We compared the beam's eye view (BEV), machine learning (ML), log (addition error: AE), and log (root sum square: RSS) methods. Log (AE) and log (RSS) were calculated from log files. These tracking errors were compared, and the optimal evaluation method was ascertained. A t-test was performed to evaluate statistically significant differences. Here, the significance level was set at 5%. RESULTS: The mean values of BEV, log (AE), log (RSS), and ML were 2.87, 3.91, 2.91, and 3.74 mm, respectively. The log (AE) and ML were higher than BEV (p < 0.001), and log (RSS) was equivalent to the BEV, suggesting that the log (RSS) calculated with the log file method can substitute for the BEV calculated with the BEV method. As RSS error calculation is simpler than BEV calculation, using it may improve clinical practice throughput. CONCLUSION: This study clarified differences among three tracking error evaluation methods for dynamic tumor tracking radiotherapy using a robotic radiosurgery system. The log (RSS) calculated by the log file method was found to be the best alternative to BEV method, as it can calculate tracking errors more easily than the BEV method.

Constrained control using novel nonlinear mapping for underactuated unmanned surface vehicles with unknown sideslip angle.

This paper addresses the problem of guidance and control for underactuated unmanned surface vehicles (USVs) with state constraints and input saturation, in support of enabling an underactuated USV to follow a parameterized curved path in the case of unknown sideslip angle and cross-tracking error constraint. First, a cross-tracking error constraint line-of-sight (LOS) guidance law with sideslip angle compensation is originally designed to guide an underactuated USV to convergence to the desired path within a time-varying cross-tracking error constraint. Second, a novel nonlinear mapping (NM) function is first constructed to map the heading and surge control subsystems with state constraints to unconstrained nonlinear systems, transforming the constrained control problem into the unconstrained control problem. Subsequently, adaptive fuzzy control laws are designed to achieve the control objectives for the USV using the new unconstrained nonlinear systems with unknown disturbance and input saturation. Then, a series of theoretical analyses using input-to-state stability theories are presented to prove the boundness of the tracking errors for the underactuated USV during path following. Finally, numerical results obtained using a physics-based simulation model are shown to reveal the effectiveness of the guidance and control algorithms.

ANFIS and ANN models to predict heliostat tracking errors.

The efficiency and performance of solar tower power are greatly influenced by the heliostats field. To ensure accurate tracking of reflectors often requires an evaluation of the beam reflected positions. This operation is costly time-consuming due to the number of heliostats. It is also necessary to set up a fast and less expensive method able to evaluate tracking heliostat. In this paper, prediction models based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) were applied to estimate rapidly and accurately heliostat error tracking. The modeling is based on the experimental data of seven different days. The input parameters are time and day number and the output is the beam reflected position following the altitude and azimuth axes. Both techniques have been able to predict the beam reflected position. A comparison of results showed that intelligent methods recorded better performance than conventional model based on geometric errors. For ANFIS model, coefficients of correlation (R2) of 0.97 is obtained compared to that of the ANN, 0.96 and 0.92 for altitude and azimuth axes respectively. The intelligent methods may be a promising alternative for predicting heliostat beam reflected the position.

Model predictive control of three-phase voltage-source converters with improved tracking performance.

The conventional finite control set-model predictive control (FCS-MPC) has not been completely embraced by the power industry because of large tracking errors and the high required sampling frequency. Therefore, the double-vector-based model predictive control (DVB-MPC), which enfolds the deadbeat control (DBC) theory, has gradually crept into researchers' horizons in recent years. In the universal DVB-MPC (UDVB-MPC) scheme, selecting two operation vectors in a single sector is a major obstacle to achieving satisfactory tracking performance. There is still a biggish error between the synthesized output voltage and the reference value. To alleviate this issue, this paper proposes an improved double-vector-based model predictive control (IDVB-MPC) scheme. The tracking errors are reduced dramatically by adding two extra vectors in adjacent sectors to the candidate set and dividing a sector into eight zones. Then the power fluctuation is reduced and the grid-connected current quality is improved. To verify the effectiveness of the proposed scheme, the simulation and experiment comparisons between UDVB-MPC and IDVB-MPC are carried out. The results show that IDVB-MPC reduces the quantitative tracking errors, the THD of the output currents, and the quantitative active power ripple by about 50%, 20%, and 35% with UDVB-MPC as a benchmark, respectively.

Highly Efficient Four-Rod Pumping Approach for the Most Stable Solar Laser Emission.

We report a significant numerical improvement in multi-rod laser efficiency, with an enhanced solar tracking error compensation capacity for a heliostat-parabolic system. The solar laser head was composed of a fused silica conical lens and a single conical pump cavity ensuring multiple passes through four 4.55 mm diameter, 15 mm length Nd:YAG rods. 0.76° tracking error width at 10% laser power loss, and total multimode laser power variation of 0.05% at ±0.1° solar tracking error and 0.30% at ±0.2° solar tracking error were numerically calculated, being 1.27, 74.80 and 21.63 times, respectively, more than the experimental record in solar tracking error compensation capacity attained with a dual-rod side-pumping horizontal prototype pumped by the same heliostat-parabolic system. Additionally, the end-side-pumping configuration of the four-rod solar laser-enabled 43.7 W total multimode solar laser power, leading to 24.7 W/m2 collection efficiency and 2.6% solar-to-laser power conversion efficiency, being 1.75 and 1.44 times, respectively, more than that experimentally obtained from the dual-rod side-pumping prototype. The significant improvement in solar tracking error compensation capacity with a highly efficient end-side-pumping configuration is meaningful because it reduces the cost of high-precision trackers for solar laser applications.

Control of Time Delay Force Feedback Teleoperation System With Finite Time Convergence.

In order to make the teleoperation system more practical, it is necessary to effectively control the tracking error convergence time of the teleoperation system. By combining the terminal sliding mode control method with the neural network adaptive control method, a bilateral continuous finite time adaptive terminal sliding mode control method is designed for the combined teleoperation system. The Lyapunov theory is used to analyze the stability of the closed-loop system, and the position tracking error is able to effectively converge in time. Finally, the effectiveness of the proposed control scheme is verified by MATLAB Simulink numerical simulation, and the numerical analysis of the results shows that the method has better system performance. Compared with the traditional two-sided control method (TPDC) of PD time-delay teleoperation system, the control method in this paper has good performance, improves stability, and makes steady-state errors smaller and better tracking.

Variable Impedance Control Based on Target Position and Tracking Error for Rehabilitation Robots During a Reaching Task.

To obtain an anthropomorphic performance in physical human-robot interaction during a reaching task, a variable impedance control (vIC) algorithm with human-like characteristics is proposed in this article. The damping value of the proposed method is varied with the target position as well as through the tracking error. The proposed control algorithm is compared with the impedance control algorithm with constant parameters (IC) and another vIC algorithm, which is only changed with the tracking error (vIC-e). The different control algorithms are validated through the simulation study, and are experimentally implemented on a cable-driven rehabilitation robot. The results show that the proposed vIC can improve the tracking accuracy and trajectory smoothness, and reduce the interaction force at the same time.

Establishing Task-Relevant MVC Protocols for Modelling Sustained Isometric Force Variability: A Manual Control Study.

The present study examined how prevalent methods for determining maximal voluntary contraction (MVC) impact the experimentally derived functions of graded force-force variability. Thirty-two young healthy subjects performed continuous isometric force tracking (20 s trials) at 10 target percentages (5-95% MVC) normalized to a conventional discrete-point (n = 16), or sustained (n = 16) MVC calculation. Distinct rates and magnitudes of change were observed for absolute variability (standard deviation (SD), root mean squared error (RMSE)), tracking error (RMSE, constant error (CE)), and complexity (detrended fluctuation analysis (DFA)) (all p < 0.05) of graded force fluctuations between the MVC groups. Differential performance strategies were observed beyond ~65% MVC, with the discrete-point group minimizing their SD at force values below that of the criterion target (higher CE/RMSE). Moreover, the sustained group's capacity to minimize SD/RMSE/CE corresponded to a more complex structure in their force fluctuations. These findings reveal that the time component of MVC estimation has a direct influence on the corrective strategies supporting near-maximal manual force control. While discrete MVC protocols predominate in the study of manual strength/endurance/precision, a 1:1 MVC-task mapping appears more to be ecologically valid if visuo-motor precision outcomes are of central importance.

Development of a tracking error prediction system for the CyberKnife Synchrony Respiratory Tracking System with use of support vector regression.

PURPOSE: The accuracy of the CyberKnife Synchrony Respiratory Tracking System is dependent on the breathing pattern of a patient. Therefore, the tracking error in each patient must be determined. Support vector regression (SVR) can be used to easily identify the tracking error in each patient. This study aimed to develop a system with SVR that can predict tracking error according to a patient's respiratory waveform. METHODS: Datasets of the respiratory waveforms of 93 patients were obtained. The feature variables were variation in respiration amplitude, tumor velocity, and phase shift between tumor and the chest wall, and the target variable was tracking error. A learning model was evaluated with tenfold cross-validation. We documented the difference between the predicted and actual tracking errors and assessed the correlation coefficient and coefficient of determination. RESULTS: The average difference and maximum difference between the actual and predicted tracking errors were 0.57 ± 0.63 mm and 2.1 mm, respectively. The correlation coefficient and coefficient of determination were 0.86 and 0.74, respectively. CONCLUSION: We developed a system for obtaining tracking error by using SVR. The accuracy of such a system is clinically useful. Moreover, the system can easily evaluate tracking error. We developed a system that can be used to predict the tracking error of SRTS in the CyberKnife Robotic Radiosurgery System using machine learning. The feature variables were the breathing parameters, and the target variable was the tracking error. We used support vector regression algorithm.

Comparing accuracy of fish sperm motility measurements obtained from two computational extremes in tracking approaches: Nearest neighbor and multiple hypothesis tracking.

We conducted a study to assess the accuracy of nearest neighbour (NN) and multiple hypothesis tracking (MHT) methods-which are opposite extremes in computational complexity-in determining the percentage of motile sperms and the number of sperms tracked in simulated data of fish sperm movements, and to evaluate the resulting number of tracking errors and analysis duration. Sperm tracking and swimming path assembly were assessed in 36 video clips (1 s length at 100 fps) of emulated Rhamdia quelen sperm kinetics at different densities (50, 100, 200 or 300 spermatozoa in the field of view) and motility rates (30, 60 or 90%). The MHT method accurately estimated the percentage of motile sperms, whereas NN underestimated it by up to 6.59%. Increase in sperm density reduced the number of sperms tracked from both trackers. With more than 50 sperms in the field of view, NN and MHT tracked 73% and 92% of the ground-truth sperm count, respectively. Both trackers showed a quadratic increase in tracking errors with increasing sperm density. The maximum percentage of errors at 90% motility was 12% for NN and 4.7% for MHT. The MHT tracker required up to 150 s to track 300 sperms, whereas NN completed the tracking procedure in less than 0.5 s. On maintaining a density of up to 100 sperms in the field of view, it was possible to obtain high accuracy, low number of tracking errors and an acceptable analysis duration with both tracking methods.

Analysis of the influence of tracking error of Xsight lung tracking system caused by cardiac beating / 中华放射肿瘤学杂志

Objective:To analyze the influence of tracking error of Xsight lung tracking system caused by cardiac beating.Methods:48 patients with lung tumors adjacent to the heart were enrolled into this study. The tumor movement curves were collected by the Xsight lung tracking system and recorded in the treatment log files during the Cyberknife treatment process. The curves were subject to filtering analysis and the respiratory motion of < 1 Hz and the cardiac beating motion of > 1 Hz were separated. According to the filtering results, the patient treatment tracking data were divided into two groups based on whether the cardiac beating wave of >1 Hz existed. The tracking errors were statistically compared between two groups based on the X-ray imaging data collected by Xsight lung tracking system during treatment.Results:For the fractionation with cardiac beat information, the tracking errors of the patient′s related models were (1.45 ± 0.99), (0.46 ± 0.21) and (0.70 ± 0.54) mm in the left-right, superior-inferior and anterior-posterior direction, respectively. For the fractionation without cardiac beat information, the tracking errors of the patient′s related models were (1.52 ± 1.17), (0.63 ± 0.37) and (1.07 ± 0.62) mm in the left-right, superior-inferior and anterior-posterior direction, respectively. The tracking errors in the superior-inferior and anterior-posterior direction of patients with accurate cardiac beat models were 28.34% and 34.86% less than those of their counterparts without accurate cardiac beat models and there was significant difference (both P<0.05). Conclusion:The tracking accuracy of Xsight lung tracking system will be significantly improved if the cardiac beat model is accurately established.

Neural Efficiency of Human-Robotic Feedback Modalities Under Stress Differs With Gender.

Sensory feedback, which can be presented in different modalities - single and combined, aids task performance in human-robotic interaction (HRI). However, combining feedback modalities does not always lead to optimal performance. Indeed, it is not known how feedback modalities affect operator performance under stress. Furthermore, there is limited information on how feedback affects neural processes differently for males and females and under stress. This is a critical gap in the literature, particularly in the domain of surgical robotics, where surgeons are under challenging socio-technical environments that burden them physiologically. In the present study, we posited operator performance as the summation of task performance and neurophysiological cost of maintaining that performance. In a within-subject design, we used functional near-infrared spectroscopy to assess cerebral activations of 12 participants who underwent a 3D manipulation task within a virtual environment with concurrent feedback (visual and visual + haptic) in the presence and absence of a cognitive stressor. Cognitive stress was induced with the serial-7 subtraction test. We found that while task performance was higher with visual than visual + haptic feedback, it degraded under stress. The two feedback modalities were found to be associated with varying neural activities and neural efficiencies, and these were stress- and gender-dependent. Our findings engender further investigation into effectiveness of feedback modalities on males and females under stressful conditions in HRI.

Reducing the tracking drift of an uncontoured tumor for a portal-image-based dynamically adapted conformal radiotherapy treatment.

Accurate tracking of organ motion during treatment is needed to improve the efficacy of radiation therapy. This work investigates the feasibility of tracking an uncontoured target using the motion detected within a moving treatment aperture. Tracking was achieved with a weighted optical flow algorithm, and three different techniques for updating the reference image were evaluated. The accuracy and susceptibility of each approach to the accumulation of position errors were verified using a 3D-printed tumor (mounted on an actuator) and a virtual treatment aperture. Tumor motion up to 15.8 mm (peak-to-peak) taken from the breathing patterns of seven lung cancer patients was acquired using an amorphous silicon portal imager at ~ 7.5 frames/s. The first approach (INI) used the initial image detected, as a fixed reference, to determine the target motion for each new incoming image, and performed the best with the smallest errors. This method was also the most robust against the accumulation of position errors. Mean absolute errors of 0.16, 0.32, and 0.38 mm were obtained for the three methods, respectively. Although the errors are comparable to other tracking methods, the proposed method does not require prior knowledge of the tumor shape and does not need a tumor template or contour for tracking. Graphical abstract.

Postural Control Underlying Head Movements While Tracking Visual Targets.

The aim of this study was to investigate the relationship between postural regulation and tracking accuracy under static and moving visual target conditions in unipedal and bipedal standing postures. Postural time-to-contact stability boundaries decreased under more challenging visual target conditions for the unipedal posture, but this decrease was associated with lower visual tracking error. During bipedal support, there was independent control of the head and foot center of pressure, as higher frequencies at the head during the static visual task were associated with longer time-to-contact. These results demonstrate that decreased time-to-contact stability boundaries is a functional adaptation in postural tasks requiring visual control and provide evidence of the dependency of postural control on the nature of the suprapostural task.

Study of the Operational Safety of a Vascular Interventional Surgical Robotic System.

This paper proposes an operation safety early warning system based on LabView (2014, National Instruments Corporation, Austin, TX, USA) for vascular interventional surgery (VIS) robotic system. The system not only provides intuitive visual feedback information for the surgeon, but also has a safety early warning function. It is well known that blood vessels differ in their ability to withstand stress in different age groups, therefore, the operation safety early warning system based on LabView has a vascular safety threshold function that changes in real-time, which can be oriented to different age groups of patients and a broader applicable scope. In addition, the tracing performance of the slave manipulator to the master manipulator is also an important index for operation safety. Therefore, we also transformed the slave manipulator and integrated the displacement error compensation algorithm in order to improve the tracking ability of the slave manipulator to the master manipulator and reduce master⁻slave tracking errors. We performed experiments "in vitro" to validate the proposed system. According to previous studies, 0.12 N is the maximum force when the blood vessel wall has been penetrated. Experimental results showed that the proposed operation safety early warning system based on LabView combined with operating force feedback can effectively avoid excessive collisions between the surgical catheter and vessel wall to avoid vascular puncture. The force feedback error of the proposed system is maintained between ±20 mN, which is within the allowable safety range and meets our design requirements. Therefore, the proposed system can ensure the safety of surgery.

A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output.

We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator's estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered.

Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy.

A direct adaptive robust tracking control is proposed for trajectory tracking of 6 DOF industrial robot in the presence of parametric uncertainties, external disturbances and uncertain nonlinearities. The controller is designed based on the dynamic characteristics in the working space of the end-effector of the 6 DOF robot. The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory. A projection-type parametric adaptation law is also designed to compensate for parametric estimation errors for the adaptive robust control. The feasibility and effectiveness of the proposed direct adaptive robust control law and the associated projection-type parametric adaptation law have been comparatively evaluated based on two 6 DOF industrial robots. The test results demonstrate that the proposed control can be employed to better maintain the desired trajectory tracking even in the presence of large parametric uncertainties and external disturbances as compared with PD controller and nonlinear controller. The parametric estimates also eventually converge to the real values along with the convergence of tracking errors, which further validate the effectiveness of the proposed parametric adaption law.

Estimation of surgical tool-tip tracking error distribution in coordinate reference frame involving pivot calibration uncertainty.

Accurate understanding of surgical tool-tip tracking error is important for decision making in image-guided surgery. In this Letter, the authors present a novel method to estimate/model surgical tool-tip tracking error in which they take pivot calibration uncertainty into consideration. First, a new type of error that is referred to as total target registration error (TTRE) is formally defined in a single-rigid registration. Target localisation error (TLE) in two spaces to be registered is considered in proposed TTRE formulation. With first-order approximation in fiducial localisation error (FLE) or TLE magnitude, TTRE statistics (mean, covariance matrix and root-mean-square (RMS)) are then derived. Second, surgical tool-tip tracking error in optical tracking system (OTS) frame is formulated using TTRE when pivot calibration uncertainty is considered. Finally, TTRE statistics of tool-tip in OTS frame are then propagated relative to a coordinate reference frame (CRF) rigid-body. Monte Carlo simulations are conducted to validate the proposed error model. The percentage passing statistical tests that there is no difference between simulated and theoretical mean and covariance matrix of tool-tip tracking error in CRF space is more than 90% in all test cases. The RMS percentage difference between simulated and theoretical tool-tip tracking error in CRF space is within 5% in all test cases.

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.