Accurate Compensation Research Articles

Active Compensation Technology for the Target Measurement Error of Two-Axis Electro-Optical Measurement Equipment.

For two-axis electro-optical measurement equipment, there are many error sources in parts manufacturing, assembly, sensors, calibration, and so on, which cause some random errors in the final measurement results of the target. In order to eliminate the random measurement error as much as possible and improve the measurement accuracy, an active compensation technique for target measurement error is proposed in this paper. Firstly, the error formation mechanism and error transfer model establishment of the two-axis electro-optical measurement equipment were studied, and based on that, three error compensation and correction methods were proposed: the least square (LS)-based error compensation method, adaptive Kalman filter(AKF)-based error correction method, and radial basis function neural network (RBFNN)-based error compensation method. According to the theoretical analysis and numerical simulation comparison, the proposed RBFNN-based error compensation method was identified as the optimal error compensation method, which can approximate the random error space surface more precisely, so that a more accurate error compensation value can be obtained, and in order to improve the measurement accuracy with higher precision. Finally, the experimental results proved that the proposed active compensation technology was valid in engineering applicability and could efficiently enhance the measurement accuracy of the two-axis electro-optical measurement equipment.

A flexible compensation device for single-phase-to-ground fault in distribution networks based on double-loop passivity-based control

Aiming at the problem that the existing single-phase-to-ground fault flexible compensation device has low compensation accuracy, long response time, and needs DC side power supply, a flexible compensation device based on double-loop passivity-based control is proposed. Firstly, the topology and working principle of the device are analyzed. And a compensation current distribution method of the bridge arm is proposed. Secondly, a double-loop passivity-based controller is designed. Finally, the proposed method is verified by MATLAB/Simulink software and 10 kV physical simulation system of distribution network. The comparisons between double-loop passivity-based control, passivity-based control, and proportional integration control is discussed. The result shows that the proposed method can accurately and rapidly compensate the fault current.

AEKF-based trajectory-error compensation of knee exoskeleton for human–exoskeleton interaction control

PurposeThe purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.Design/methodology/approachA trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.FindingsSix volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.Originality/valueThe AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

Thermal error compensation in length inspection of large-scale aircraft spars in nonuniform temperature environments

As the primary load-bearing structures, large-scale aircraft spars are subject to the influence of nonuniform temperatures in field conditions, resulting in thermal errors during on-site length inspections. These errors require accurate compensation. Conventional linear scaling methods, based on the assumption of uniform temperatures and a retrieved coefficient of thermal expansion (CTE), suffer from low accuracy in nonuniform temperature environments. To address this issue, this paper proposed a thermal error compensation method that incorporates CTE recalibration. First, we established a predictive model for thermal errors in nonuniform temperature fields through differential thermoelastic analysis. Secondly, a recalibration technique for the sensitive parameter, CTE, was introduced to enhance the prediction accuracy. Finally, leveraging the equivalent form of the model, an uncertainty assessment approach tailored for nonuniform temperature conditions was formulated for the compensated lengths. Numerical and case studies of a nearly 1 m long simplified wing spar were implemented to validate the performance of the thermal error compensation method. The results indicate that the presented method improved accuracy by over 57.6% in terms of RMSE compared to the linear scaling method using average temperatures, which would provide a viable approach to achieve a more accurate on-site length inspection of aircraft components.

Optimal proportion compensation method of key geometric errors for five-axis machine tools considering multiple-direction coupling effects

Five-axis machine tools are subject to highly coupled geometric errors that significantly affect their machining accuracy. Existing geometric error compensation methods do not consider the coupling effects between errors, resulting in insufficient error compensation efficiency and accuracy. To solve this problem, an optimal proportion compensation method for key geometric errors of five-axis machine tools was proposed, considering multiple direction coupling effects. The key geometric errors were identified using the improved Sobol method based on the volumetric error model. The coupling effects of the geometric errors were analyzed based on the overlapping terms of the key errors in multiple directions, and the coupling situation was classified into four types. The compensation sequence and proportion value in each direction were developed according to the coupling type; i.e., the key errors were compensated to the proportion value instead of the traditional compensation to zero. Taking the S-shaped specimen as an example, the experimental verification indicated that the number of geometric error items that had to be compensated by our method was reduced by 44.4 % compared to the traditional key geometric error compensation method. Additionally, the compensation accuracy was increased by 58.9 %, thus proving the effectiveness of the proposed method.

Motion Hysteresis Compensation Based on Motor Current Segmentation for Elongated Cable-Driven Surgical Instruments

Cable-driven surgical instrument is a reusable and disposable component of Robot-assisted Minimally Invasive Surgery, and it is time-consuming to identify the motion hysteresis compensation model of each instrument in large-scale identification. Besides, the identification results failure caused by the loss of cable tension or lubrication conditions during repeated usage interferes with the accuracy of motion hysteresis compensation. To simplify the identification process and lengthen the instrument life, this paper leverages the relationship between actuate motor current and hysteresis phases, developing a novel motion hysteresis compensation method to compensate the motor reference trajectory. Firstly, prior knowledges including motor current and hysteresis curves of several instruments are collected to train the Hysteresis Identification model and Curve Generation model. Once the two models are well-trained in practical use, the only sensor data in need is the motor current for the Hysteresis Identification model, and the compensation curve will be generated pertinently for the instrument under current use. Finally, Feedforward Compensation scheme is conducted to compensate the reference trajectory of the actuate motor. Experiments study the range of hysteresis compensation errors when the method is applied to numerous surgical instruments with different motion hysteresis, and the feasibility and accuracy are verified. The method can be potentially applied to a wide range of cable-driven mechanisms facing the problem of large-scale identification or the identification results failure after repeated use. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper proposes a feasible motion hysteresis compensation method for cable-driven mechanism (CDM). For some CDMs like elongated cable-driven surgical instrument, their motion hysteresis characteristics will change during repeated use, and their distal angle and cable tension are not available in the environment of use. In these cases, the proposed method enables re-identification because the distal angle or cable tension are not needed during the practical use of our method. Besides, it is easy and low-cost for large-scale identification due to the simplicity of identification procedure. Once the Hysteresis Identification model and Curve Generation model are trained using the pre-collected prior knowledge including motor current and the angle of the end effector, the only sensor data in need to identify and compensate a certain CDM is the its motor current. Then, the pertinent compensation curve for the CDM device can be generated for the actuate motor to follow. The experimental results reveal that the competitive performance with other state-of-the-arts can be achieved. In the future research, we will integrate dynamic characteristics of CDM into the method to expand the scope of application.

Benefits of Planter Turn Compensation on Irregular Shaped Fields

Highlights For the production fields examined, turn compensation was actuated for between 4.7% and 12.1% of the area during planting operations. Seeding rate error without turn compensation ranged from 30.9% to 570.1% while with turn compensation seeding rate error was only 0.1% to 10.4%. A cost savings of $16 to $212 ha-1 can be realized when planting with a turn compensation feature. Abstract. Modern precision planters utilize advanced technologies such as electric seed metering units and hydraulic downforce systems, allowing for more precise control of seed placement during planting. This study focused on assessing the effectiveness of adopting turn compensation using electrically driven seed meters. Turn compensation refers to the ability of a planter to adjust seeding rates across the toolbar to account for the speed differential caused by planting around a turn or curvilinear pass. Significant research has been conducted on the accuracy of turn compensation implemented by electric driven seed meters, though no existing research could be found on the amount of ground covered in a production field when the technology is being utilized. Thus, the objectives of this study are: 1) to quantify the extent of area planted with turn compensation actuated on fields with varying size and shape and 2) to assess the potential cost savings when using a planter equipped with this technology. Results indicated that turn compensation could provide accurate adjustments of seed and fertilizer inputs while planting on curvilinear paths. In the production fields examined turn compensation would be actuated on between 4.7% and 12.1% of the area. Spacing data confirmed that the turn compensation accurately corrected the seed spacing when planting on curves. Seeding rate error without turn compensation ranged from 30.9% to 570.1% while with turn compensation seeding rate error was only 0.1% to 10.4%. Finally, results indicated a cost savings of $16 to $212 ha-1 when using a planter with a turn compensation feature.

A gradient-based approach to fast and accurate head motion compensation in cone-beam CT.

Cone-beam computed tomography (CBCT) systems, with their flexibility, present a promising avenue for direct point-of-care medical imaging, particularly in critical scenarios such as acute stroke assessment. However, the integration of CBCT into clinical workflows faces challenges, primarily linked to long scan duration resulting in patient motion during scanning and leading to image quality degradation in the reconstructed volumes. This paper introduces a novel approach to CBCT motion estimation using a gradient-based optimization algorithm, which leverages generalized derivatives of the backprojection operator for cone-beam CT geometries. Building on that, a fully differentiable target function is formulated which grades the quality of the current motion estimate in reconstruction space. We drastically accelerate motion estimation yielding a 19-fold speed-up compared to existing methods. Additionally, we investigate the architecture of networks used for quality metric regression and propose predicting voxel-wise quality maps, favoring autoencoder-like architectures over contracting ones. This modification improves gradient flow, leading to more accurate motion estimation. The presented method is evaluated through realistic experiments on head anatomy. It achieves a reduction in reprojection error from an initial average of 3 mm to 0.61 mm after motion compensation and consistently demonstrates superior performance compared to existing approaches. The analytic Jacobian for the backprojection operation, which is at the core of the proposed method, is made publicly available. In summary, this paper contributes to the advancement of CBCT integration into clinical workflows by proposing a robust motion estimation approach that enhances efficiency and accuracy, addressing critical challenges in time-sensitive scenarios.

MC-VEO: A Visual-Event Odometry With Accurate 6-DoF Motion Compensation

MC-VEO: A Visual-Event Odometry With Accurate 6-DoF Motion Compensation

Thermal displacement prediction of variable preload motorized spindles based on speed reduction experiments and IABC-BP optimization models

The thermal error caused during the high-speed operation of a high-speed motorized spindle has a significant impact on machine tool precision. In this paper, we firstly built, constructed an experimental platform for variable voltage preloaded motorized spindle, used the natural deceleration experimental method to ascertain the spindle's thermal displacement and temperature information when bearing preload is 1400 N, 1450 N, 1550 N and 1700 N, and combined with the thermoelasticity theoretical analysis, the thermal displacement of affected by the heat generation of motor and bearing was separated, and a new artificial bee colony algorithm-optimized BP neural network-based thermal error prediction model has been presented. The thermal displacements of the spindles are separated and a BP neural network optimization of a novel thermal error prediction model based on Improved Artificial Bee Colony Algorithm (IABC-BP) is proposed for transformer preloaded spindles. Combined with the experimental data of bearing preload of 1400 N, the thermal displacements of the spindle at preloads of 1450 N, 1550 N and 1700 N are predicted, and the evaluation indexes obtained from the simulation of the BP, ABC-BP, and IABC-BP models are compared. absolute error (MAE) and root-mean-square error (RMSE), higher goodness-of-fit (R2), and 20.37 % lower mean absolute error and 26.83 % lower root-mean-square error compared with the traditional thermal error prediction model. The IABC-BP prediction model proposed in this paper provides a more accurate compensation method for transformer preloaded spindles.

Online distributed waveform-synchronization for acoustic sensor networks with dynamic topology

Acoustic sensing by multiple devices connected in a wireless acoustic sensor network (WASN) creates new opportunities for multichannel signal processing. However, the autonomy of agents in such a network still necessitates the alignment of sensor signals to a common sampling rate. It has been demonstrated that waveform-based estimation of sampling rate offset (SRO) between any node pair can be retrieved from asynchronous signals already exchanged in the network, but connected online operation for network-wide distributed sampling-time synchronization still presents an open research task. This is especially true if the WASN experiences topology changes due to failure or appearance of nodes or connections. In this work, we rely on an online waveform-based closed-loop SRO estimation and compensation unit for nodes pairs. For WASNs hierarchically organized as a directed minimum spanning tree (MST), it is then shown how local synchronization propagates network-wide from the root node to the leaves. Moreover, we propose a network protocol for sustaining an existing network-wide synchronization in case of local topology changes. In doing so, the dynamic WASN maintains the MST topology after reorganization to support continued operation with minimum node distances. Experimental evaluation in a simulated apartment with several rooms proves the ability of our methods to reach and sustain accurate SRO estimation and compensation in dynamic WASNs.

Joint determination of Venus gravity and atmospheric density through EnVision radio science investigation

The ESA mission EnVision will address its main scientific questions through a detailed mapping of the surface and interior properties of Venus. A precise reconstruction of the spacecraft trajectory is a key requirement for the EnVision scientific investigations, including radio science. To precisely constrain the orbit evolution, refined models of the dynamical forces are included in the Precise Orbit Determination (POD) process. We developed a methodology based on a batch-sequential filter that enables a joint estimation of Venus gravity and atmospheric density. Our approach yields an accurate compensation of atmospheric mismodeling, simulated through semi-empirical predictions of the atmospheric density provided by general circulation models (GCM), e.g., Venus Climate Database (VCD). Numerical simulations of the EnVision radio science investigation were carried out by using a perturbative analysis of the dynamical forces, which accounts for atmospheric density errors ≥ 200%. By adjusting a set of atmospheric scale factors, our proposed strategy enables an estimation of the atmospheric density at the spacecraft altitudes with an accuracy of 25%. The improved dynamical model yields accuracies in the orbit reconstruction of 1–2 m, 30–40 m and 20–30 m in the radial, transverse and normal directions.

Automatic and accurate compensation for phase aberrations in digital holographic microscopy based on iteratively reweighted least squares fitting

Phase aberrations must be precisely compensated for phase-contrast imaging in digital holographic microscopy. In this paper, an automatic and accurate phase aberration compensation method is proposed based on iteratively reweighted least squares fitting. Instead of selecting the known-to-be-flat region with manual operation or image segmentation, this method starts from conventional least squares fitting in the whole image and attributes lower weights to the pixels with higher fitting residuals in an iterative reweighting procedure, during which the influence of specimen and noise is automatically reduced. Both phase curvature and high-order aberrations could be corrected without extra operation. Numerical simulation demonstrates that the proposed method is more accurate than the state-of-the-art numerical methods. Experimental result proves that this method is robust and fast enough for dynamic imaging of living cells.

Symptoms in unilateral vestibular hypofunction are associated with number of catch-up saccades and retinal error: results from the population-based KORA FF4 study

ObjectiveThe presence and intensity of symptoms vary in patients with unilateral vestibular hypofunction. We aimed to determine which saccadic and vestibulo-ocular reflex parameters best predict the presence of symptoms in unilateral vestibular hypofunction in order to better understand vestibular compensation and its implications for rehabilitation therapy.MethodsVideo head impulse test data were analyzed from a subpopulation of 23 symptomatic and 10 currently symptom-free participants with unilateral vestibular hypofunction, embedded in the KORA (Cooperative Health Research in the Region of Augsburg) FF4 study, the second follow-up of the KORA S4 population-based health survey (2,279 participants).ResultsA higher number of catch-up saccades, a higher percentage of covert saccades, and a larger retinal error at 200 ms after the onset of the head impulse were associated with relevant symptoms in participants with unilateral vestibular hypofunction (p = 0.028, p = 0.046, and p = 0.038, respectively). After stepwise selection, the number of catch-up saccades and retinal error at 200 ms remained in the final logistic regression model, which was significantly better than a null model (p = 0.014). Age, gender, saccade amplitude, saccade latency, and VOR gain were not predictive of the presence of symptoms.ConclusionThe accuracy of saccadic compensation seems to be crucial for the presence of symptoms in unilateral vestibular hypofunction, highlighting the role of specific gaze stabilization exercises in rehabilitation. Early saccades, mainly triggered by the vestibular system, do not seem to compensate accurately enough, resulting in a relevant retinal error and the need for more as well as more accurate catch-up saccades, probably triggered by the visual system.

Research on 2D Image Motion Compensation for a Wide-Field Scanning Imaging System with Moving Base

The wide-field imaging system carried on a high-altitude or near-space vehicle takes high-resolution images of the ground to measure and map targets. With the improvement of imaging resolution and measurement accuracy, the focal length of the wide-field imaging system is getting longer. The requirement for image motion compensation (IMC) accuracy is getting higher, and the influence of optical path coupling is increasing within the process of two-dimensional (2D) IMC. To further improve the IMC accuracy of the wide-field imaging system, an innovative IMC method is first proposed in this paper. The method is based on the 2D motion of the scanning platform and secondary mirror. Secondly, to solve the optical coupling problem in the process of 2D IMC, the coupling phenomenon is analyzed. The coupling relationships between 2D scanning motion, 2D secondary mirror motion and image motion is derived from the compensation process. A complete 2D IMC model is established, and a 2D IMC method, including an optical path decoupling correct regulator (ODCR), is designed. Finally, the method is verified in laboratory and field flight tests. The results show that the proposed method can effectively correct the coupling error of the optical path in the process of IMC and achieve high-resolution 2D IMC. When the scanning speed is 60°/s and the exposure time is 2 ms, the accuracy of the 2D IMC is up to 0.57pixels (RMS) in the pitch direction, and 0.46 pixels (RMS) in the roll direction.

An improved predictor LOS-based global fixed-time prescribed performance controller for the path following of underactuated marine surface vehicles with input saturation

A fixed-time controller based on improved fixed-time predictor line-of-sight (FxTPLOS) guidance and a nonsymmetrical prescribed performance constrained controller is designed for the path-following of underactuated marine surface vehicles (MSVs) in the presence of unknown external disturbances and uncertainties. First, a fixed-time error prediction model is established, and an internal model-controlled observer is designed to observe the sideslip angle, which can extend the estimated range of the sideslip angle to any range. Second, a nonlogarithmic performance function is introduced that can converge the error to a prescribed range, and a fixed-time controller is designed by error transformation. A new input saturation function is added to solve the problem of input saturation, and a new filter is added to avoid differentiating the virtual control law. Third, a novel fixed-time lumped disturbance observer is proposed for estimating the model uncertainty and external disturbances. It is possible to achieve accurate disturbance compensation. By using Lyapunov theory to analyze the stability of the closed-loop control system, it is proven that the system can be uniformly globally fixed-time stable (UGFxTS). Finally, simulation experiments prove that the control strategy proposed in this paper is effective.

Temperature compensation of fiber optic unbalanced interferometers for high resolution static strain sensing

Accurate temperature compensation challenges the use of fiber optic unbalanced interferometers in static strain sensing. We propose a temperature compensation theory and scheme of unbalanced interferometers using sensing fibers with different temperature coefficients, aiming at resolving the temperature disturbance of optical fibers and achieving high strain resolution. For the first time, we comprehensively analyze the thermal response of interferometers due to different temperature coefficients, different thermal behaviors, and inconsistent temperature disturbances in the optical fiber arms. A sensing combination and a reference combination are designed. The sensing combination measures a strain and compensates for the temperature disturbance of the sensing arm, and the reference combination provides a reference to compensate for the temperature disturbance of the reference arm and frequency drift of the interferometer in the sensing combination. The proposed scheme can compensate for the temperature disturbances of interferometers in the sensing combination completely. To verify the theory and scheme, bend-insensitive single-mode fibers and Boron/Germanium co-doped fibers are used as sensing fibers in the experiment. The experimental results show that the temperature resolution of the sensing arm is about 3.43 × 10−4 °C, and the static strain resolution of the unbalanced interferometer within 24 h after temperature compensation is about 2.55 nε. The temperature-compensated strain resolution of ∼nε indicates that the proposed temperature compensation theory and scheme can be used in high-resolution, long-term, low-frequency, and static strain sensing, such as crustal deformation observation in geophysical applications.

Prediction and control strategy based on optimized active disturbance rejection control for AHC system

In this paper, a novel control and prediction algorithm is proposed to solve the problem of decoupling control and response delay in the AHC system of electric winch, which effectively improves the compensation accuracy and response speed of the AHC system. The innovation of the control strategy is mainly as follows: 1) Long short-term memory (LSTM) neural network is used for predicting the ship heave motion. The Bayesian algorithm is used to optimize the hyperparameters to improve the prediction accuracy.2) In the design of the AHC controller, the main speed feedforward is used to directly govern the system's output. The position loop adopts the active disturbance rejection control (ADRC) to improve the anti-disturbance and position-tracking ability of the AHC system.3) For the numerous parameters of ADRC, the chaotic particle Swarm optimization (CPSO) algorithm is used to tune parameters. The simulation results show that the algorithm is effective in improving the robustness and compensation efficiency of the system. Finally, the experiment is carried out on the AHC experimental platform of the full-size winch. The compensation results before and after prediction are compared and analyzed.

Multichannel seismic data attenuation compensation via curvelet‐based sparsity promotion

AbstractDue to subsurface viscosity and heterogeneity, the vertical resolution of observed seismic data is decreased after wave propagation, generating nonstationary seismic data with amplitude attenuation and phase distortion. Inverse Q filtering techniques are always used to enhance the vertical resolution of seismic data. However, the majority of inverse Q filtering methods treat attenuation compensation trace by trace, which may produce non‐robust compensation results with poor transverse continuity and amplify noise energy in noisy cases. Thus, we develop a novel sparsity‐promoting inversion‐based multichannel seismic data attenuation compensation approach by introducing a sparse constraint for curvelet coefficients of multichannel compensated data, which takes the transverse continuity of compensated data into account. Besides, the proposed method with a sparse constraint for curvelet coefficients has a better noise‐resistance property, which can attenuate the noise energy in noisy cases during attenuation compensation, improving compensation accuracy and robustness. To improve its computational efficiency, a fast iterative shrinkage–thresholding algorithm is adopted to solve the established lasso problem. Synthetic data examples with different noise levels and two post‐stack field data examples validate the effectiveness of the proposed multichannel method. Its compensation results have superior vertical resolution, transverse continuity and noise robustness in comparison to the conventional single‐channel compensation method using a damped least squares algorithm.

Mamdani vs. Takagi-Sugeno Fuzzy Inference Systems in the Calibration of Continuous-Time Car-Following Models.

The transition to intelligent transportation systems (ITSs) is necessary to improve traffic flow in urban areas and reduce traffic congestion. Traffic modeling simplifies the understanding of the traffic paradigm and helps researchers to estimate traffic behavior and identify appropriate solutions for traffic control. One of the most used traffic models is the car-following model, which aims to control the movement of a vehicle based on the behavior of the vehicle ahead while ensuring collision avoidance. Differences between the simulated and observed model are present because the modeling process is affected by uncertainties. Furthermore, the measurement of traffic parameters also introduces uncertainties through measurement errors. To ensure that a simulation model fully replicates the observed model, it is necessary to have a calibration process that applies the appropriate compensation values to the simulation model parameters to reduce the differences compared to the observed model parameters. Fuzzy inference techniques proved their ability to solve uncertainties in continuous-time models. This article aims to provide a comparative analysis of the application of Mamdani and Takagi-Sugeno fuzzy inference systems (FISs) in the calibration of a continuous-time car-following model by proposing a methodology that allows for parallel data processing and the determination of the simulated model output resulting from the application of both fuzzy techniques. Evaluation of their impact on the follower vehicle considers the running distance and the dynamic safety distance based on the observed behavior of the leader vehicle. In this way, the identification of the appropriate compensation values to be applied to the input of the simulated model has a great impact on the development of autonomous driving solutions, where the real-time processing of sensor data has a crucial impact on establishing the car-following strategy while ensuring collision avoidance. This research performs a simulation experiment in Simulink (MATLAB R2023a, Natick, MA, USA: The MathWorks Inc.) and considers traffic data collected by inductive loops as parameters of the observed model. To emphasize the role of Mamdani and Takagi-Sugeno FISs, a noise injection is applied to the model parameters with the help of a band-limited white-noise Simulink block to simulate sensor measurement errors and errors introduced by the simulation process. A discussion based on performance evaluation follows the simulation experiment, and even though both techniques can be successfully applied in the calibration of the car-following models, the Takagi-Sugeno FIS provides more accurate compensation values, which leads to a closer behavior to the observed model.