Error Compensation Technique Research Articles

Closed-Form Method for Unified Far-Field and Near-Field Localization Based on TDOA and FDOA Measurements

When the near-field and far-field information of a target is uncertain, it is necessary to choose a suitable localization method. The modified polar representation (MPR) method integrates the two scenarios and achieves a unified localization with direction of arrival (DOA) estimation in the far field and position estimation in the near field. Previous studies have only proposed solutions for stationary environments and have not considered the motion factor. Therefore, this paper proposes a new unified positioning algorithm using multi-sensor time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements without prior target source information. The method represents the position of the target source using MPR and describes the localization problem as a weighted least squares (WLS) problem with two constraints. We first obtain the initial estimates by WLS without considering the constraints and then investigate a two-step error correction method based on the constraints. The first step corrects the initial estimate using the Taylor series expansion technique, and the second step corrects the DOA estimate in the previous step using the direct error compensation technique based on the properties of the second constraint. Simulation experiments show that the method is effective for the unified positioning of moving targets and can achieve the Cramer–Rao lower bound (CRLB).

Precision improvement of robotic bioprinting via vision-based tool path compensation

Robotic 3D bioprinting is a rapidly advancing technology with applications in organ fabrication, tissue restoration, and pharmaceutical testing. While the stepwise generation of organs characterizes bioprinting, challenges such as non-linear material behavior, layer shifting, and trajectory tracking are common in freeform reversible embedding of suspended hydrogels (FRESH) bioprinting, leading to imperfections in complex organ construction. To overcome these limitations, we propose a computer vision-based strategy to identify discrepancies between printed filaments and the reference robot path. Employing error compensation techniques, we generate an adjusted reference path, enhancing robotic 3D bioprinting by adapting the robot path based on vision system data. Experimental assessments confirm the reliability and agility of our vision-based robotic 3D bioprinting approach, showcasing precision in fabricating human blood vessel segments through case studies. Significantly, it minimizes the printing layer width disparity to just 0.15 mm compared to the 0.6 mm in traditional methods, and it decreases the average error for curved filaments to 7.0 mm2 from the previous 12.7 mm2 in conventional printing. While these results underscore the significant potential of our innovation in creating precise biomimetic constructs, further investigation is necessary to tackle challenges such as accurately distinguishing closely stacked layers using a vision system, especially under varying lighting conditions. These limitations, coupled with issues of computational complexity and scalability in larger-scale bioprinting, emphasize the importance of enhancing the reliability of the vision-based approach across various conditions. Nonetheless, our innovation demonstrates substantial promise in creating precise biomimetic constructs and paves the way for future advancements in vision-guided robotic bioprinting, including the integration of multi-material printing techniques to enhance versatility.

Research on six-joint industrial robotic arm positioning error compensation algorithm based on motion decomposition and improved CIWOA-BP neural network

Motion errors in the trajectory of a six-joint industrial robotic arm’s end-effector can significantly impact machining precision. Complex milling operations can lead to deviations from the intended path due to the robotic arm’s structural characteristics. These errors often exhibit periodic and position-dependent variations, underscoring the need for meticulous control measures. To address this challenge, we propose a novel motion decomposition-based error compensation technique for a six-joint industrial robotic arm. This approach involves breaking down the robot’s motion trajectory into distinct components and constructing prediction models for each component using a BP neural network. These models are then optimized using the Whale Optimization Algorithm (CIWOA) and an adaptive chaotic mapping clustering approach to improve efficiency and global optimization. The proposed method is applied to various motion types of the robotic arm, resulting in substantial enhancements in absolute positioning accuracy. Experimental validation confirms the reliability of the CIWOA-BP neural network prediction model and the effectiveness of the nonparametric accuracy compensation method in refining motion planning precision.

Research on High-speed Electric Spindle Cooling Devices and Thermal Error Compensation Technology

Background: When computerized numerical control (CNC) machine tools are working, the electric spindle generates serious heat, which can easily cause the thermal elongation of the spindle and generate thermal errors. Designing cooling devices to control the generation of thermal errors in the spindle and utilizing thermal error compensation techniques for error compensation are essential for improving machining quality and productivity. Objective: By summarizing the current status of research on cooling devices and compensation technology of electric spindles in recent years, some conclusions have been drawn in this work to propose the future research direction. Methods: By reviewing patents on cooling devices and thermal error compensation technology of high-speed electric spindles published in recent years, we have explored the ideas for the improvement of existing cooling devices and compensation technology. Results: Some problems of the patents on current cooling devices and thermal error compensation technology are analyzed, and future research directions are proposed, respectively. Conclusion: As spindle power and speed continue to increase, the existing spindle cooling device and compensation technology also need to be continuously improved. Designers use intelligent technology to monitor the temperature changes during the work of the spindle and fast and accurate control of the cooling system so that the high-speed spindle cooling device tends to be intelligent. Aiming at the thermal error generated in the spindle working process, the designer enhances the error compensation effect by continuously improving and upgrading the key steps in the thermal error compensation technology, which in turn improves the spindle machining accuracy.

Wind power error compensation prediction model based on CEEMD-SE-ELM-TCN

Abstract Wind power generation holds immense importance in addressing the issue of global energy shortage, while precise wind power forecasting proves essential for effective management and dependable operation of wind power networks. This study introduces a hybrid deep learning model, encompassing complete ensemble empirical mode decomposition (CEEMD), sample entropy (SE), extreme learning machine (ELM) and time convolutional network (TCN), for accurately predicting short-term wind power output. First, CEEMD decomposed the original wind power into multiple submodes, which effectively reduced the series volatility. Then, the SE of intrinsic mode function sequence is calculated, and the subsequences with similar complexity are superimposed to reduce the calculation cost, improve the simulation accuracy and reduce the noise of the original wind power sequence. Secondly, the ELM model is established for each submode, and the prediction error of BiLSTM is predicted again using TCN to improve the efficiency and prediction performance of the hybrid model. Finally, the outcomes of each individual submode are amalgamated to yield the ultimate prediction outcome. To showcase the efficacy and dominance of the error compensation technique, several comparison models were established in the experiment. The results demonstrated that the suggested hybrid model exhibits superior predictive accuracy in the domain of wind power prediction. Compared with the comparison model, the improvement in MAPE and RMSE was 60.50 and 77.74%, respectively.

Phase Error Compensation Technique Based on Phase-Shifting Fringe Analysis: A Review (Invited)

Phase Error Compensation Technique Based on Phase-Shifting Fringe Analysis: A Review (Invited)

A conservative implicit scheme for three-dimensional steady flows of diatomic gases in all flow regimes using unstructured meshes in the physical and velocity spaces

A conservative implicit scheme in the finite volume discrete velocity method framework is proposed for solving the three-dimensional steady flows of molecular gases in all flow regimes from continuum one to free-molecular one. This work is based on the Boltzmann–Rykov model equation, which is a nonlinear relaxation model and can describe the thermodynamic non-equilibrium of diatomic gas flows. The macroscopic equations are solved implicitly together with the Rykov model equation to find a predicted equilibrium distribution first at each iteration step. As a result, the collision term of the Rykov model equation can be discretized in a fully implicit way for fast convergence in all flow regimes. At the cell interface, an asymptotic preserving simplified multi-scale numerical flux is developed to relieve the limitation of grid size and time step in all flow regimes, which can keep the multi-scale property and achieve high computational efficiency. The integral error compensation technique is used to keep the scheme conservative and greatly reduce the number of unstructured discrete velocity space (DVS) meshes. Furthermore, an empirical criterion based on the numerical experiments of the Apollo 6 command module is suggested to guide the generation of three-dimensional unstructured DVS. The accuracy and efficiency of the present method are demonstrated by a number of three-dimensional classic cases, covering different flow regimes.

Modeling and Prediction of Thermal Deformation Errors in Fiber Optic Gyroscopes Based on the TD-Model

For a fiber optic gyroscope, thermal deformation of the fiber coil can introduce additional thermal-induced phase errors, commonly referred to as thermal errors. Implementing effective thermal error compensation techniques is crucial to addressing this issue. These techniques operate based on the real-time sensing of thermal errors and subsequent correction within the output signal. Given the challenge of directly isolating thermal errors from the gyroscope’s output signal, predicting thermal errors based on temperature becomes necessary. To establish a mathematical model correlating the temperature and thermal errors, this study measured synchronized data of phase errors and angular velocity for the fiber coil under various temperature conditions, aiming to model it using data-driven methods. However, due to the difficulty of conducting tests and the limited number of data samples, direct engagement in data-driven modeling poses a risk of severe overfitting. To overcome this challenge, we propose a modeling algorithm that effectively integrates theoretical models with data, referred to as the TD-model in this paper. Initially, a theoretical analysis of the phase errors caused by thermal deformation of the fiber coil is performed. Subsequently, critical parameters, such as the thermal expansion coefficient, are determined, leading to the establishment of a theoretical model. Finally, the theoretical analysis model is incorporated as a regularization term and combined with the test data to jointly participate in the regression of model coefficients. Through experimental comparative analysis, it is shown that, relative to ordinary regression models, the TD-model effectively mitigates overfitting caused by the limited number of samples, resulting in a substantial 58% improvement in predictive accuracy.

Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting

Prediction of electricity price is crucial for national electricity markets supporting sale prices, bidding strategies, electricity dispatch, control and market volatility management. High volatility, non-stationarity and multi-seasonality of electricity prices make it significantly challenging to estimate its future trend, especially over near real-time forecast horizons. An error compensation strategy that integrates Long Short-Term Memory (LSTM) network, Convolution Neural Network (CNN) and the Variational Mode Decomposition (VMD) algorithm is proposed to predict the half-hourly step electricity prices. A prediction model incorporating VMD and CLSTM is first used to obtain an initial prediction. To improve its predictive accuracy, a novel error compensation framework, which is built using the VMD and a Random Forest Regression (RF) algorithm, is also used. The proposed VMD-CLSTM-VMD-ERCRF model is evaluated using electricity prices from Queensland, Australia. The results reveal highly accurate predictive performance for all datasets considered, including the winter, autumn, spring, summer, and yearly predictions. As compared with a predictive model without error compensation (i.e., the VMD-CLSTM model), the proposed VMD-CLSTM-VMD-ERCRF model outperforms the benchmark models. For winter, autumn, spring, summer, and yearly predictions, the average Legates and McCabe Index is seen to increase by 15.97%, 16.31%, 20.23%, 10.24%, and 14.03%, respectively, relative to the benchmark models. According to the tests performed on independent datasets, the proposed VMD-CLSTM-VMD-ERCRF model can be a practical stratagem useful for short-term, half-hourly electricity price forecasting. Therefore the research outcomes demonstrate that the proposed error compensation framework is an effective decision-support tool for improving the predictive accuracy of electricity price. It could be of practical value to energy companies, energy policymakers and national electricity market operators to develop their insight analysis, electricity distribution and market optimization strategies.

A High-Accuracy Low-Power Approximate Multipliers with New Error Compensation Technique for DSP Applications

A High-Accuracy Low-Power Approximate Multipliers with New Error Compensation Technique for DSP Applications

Decentralized online convex optimization with compressed communications

Due to the iterative information exchange between agents, decentralized multi-agent optimization algorithms often incur large communication overhead, which is not affordable in many practical systems with scarce resources. To address this communication bottleneck, we compress the exchanged information between neighboring agents to solve decentralized online convex optimization problem, where each agent has a time-varying local loss function and the goal is to minimize the accumulated global loss by choosing actions sequentially. We develop a decentralized online gradient descent algorithm based on compressed communications, where the compression operators can reduce the amount of data to be sent significantly. Error-compensation technique is utilized to mitigate the error accumulation caused by the communication compression. We further analyze the performance of the proposed algorithm. It is shown that the regret is bounded from above by O(T) (T is the time horizon), which is the same as (in order sense) the regret bound for vanilla decentralized online gradient descent with perfect communication. Thus, the proposed algorithm is capable of reducing the communication overhead remarkably without much degradation of the optimization performance. This is further corroborated by numerical experiments, where compressed communication reduces the number of transmitted bits by an order of magnitude without compromising the optimization performance.

Compensating the NLoS Occlusion Errors of UWB for Pedestrian Localization With MIMU

The Ultra-Wideband (UWB) technology has become a competitive choice for indoor pedestrian localization due to its advantages in accuracy, compact size, reliability, power efficiency, and easy setup. However, the None-Line-of-Sight (NLoS) occlusion caused by the human body parts and obstacles in its propagation path may introduce significant location errors that limit its performance and field of application. To handle the NLoS occlusion errors and promote the localization accuracy for complex indoor environments, a Micro-Electro-Mechanical System (MEMS) Inertial Measurement Unit (MIMU)-assisted UWB localization system with NLoS occlusion error compensation techniques is provided. Firstly, an NLoS occlusion detection method using the built-in channel information of the UWB transceivers and the variation pattern of anchor-node distance is proposed. Secondly, an Extended Kalman Filter (EKF)-based attitude computation and a Zero-Velocity Update (ZUPT)-based continuous gait segmentation are introduced for inertial navigation during occlusion intervals. Then, the UWB and IMU parameters are integrated with an Unscented Kalman Filter (UKF) framework to compensate for the occlusion error and improve the accuracy and robustness. Finally, a battery-powered miniature wearable device is developed and the proposed techniques are verified with experimental studies. The results demonstrate the feasibility and effectiveness of the presented techniques, which provides a good reference for related Internet of Things (IoT) applications.

Gamma error correction algorithm for phase shift profilometry based on polar angle average

Phase errors caused by the gamma nonlinear response of the phase shift profilometry (PSP) severely affect 3D measurement accuracy. To tackle this, a simple phase error compensation technique based on polar angle average is presented in this paper to improve the accuracy. Wrapped phase values are regarded as polar angles, and a polar axis distribution map can be obtained in the polar coordinate. Practically, the polar axis distribution (PAD) of the undistorted wrapped phase is uniform. When there are nonlinear effects in an PSP, the polar axis is unevenly distributed. The difference between adjacent polar angles is computed and then rearranged with specifically labels. After that, the even PAD diagram is generated, and the smooth phase can be further recovered. Compared with conventional nonlinearity correction methods, the proposed method corrects the error without any auxiliary conditions. Its effectiveness and robustness are verified in simulations and experiments.

Pose accuracy improvement in robotic machining by visually-guided method and experimental investigation

Industrial robots have been widely used in the industries of automotive, machining, electrical and electronic, rubber and plastics, aerospace, food, etc., owing to their high efficiency and flexibility in contrast to large scaled machining centers. However, the poor accuracy resulted from the serial configuration of industrial robots has restricted their applications to high-precision machining for several decades. In this paper, an error compensation technique is proposed using the visual guidance to effectively improve the pose accuracy of industrial robots. Firstly, the effect of the establishment method of tracking coordinate system for a visual sensor on the pose measurement error is analyzed and the establishment method is optimized. Next, a fuzzy PID controller is designed and integrated with a KUKA robot controller KRC via the KUKA robot sensor interface to guide the robot to the desired pose in real-time. Finally, experimental tests are implemented to validate the effectiveness of the proposed approach.

Multiplicative and Additive Error Compensation Techniques for Perfect Reference Tracking

This paper introduces a novel approach to supply reference inputs to feedback systems. In this approach, modified inputs are used to ensure enhancing the capability of the system to achieve the actual desired inputs. Traditionally, the difference between the reference inputs to a system and the outputs are used to decide the suitable correcting actions. In this paper, modified reference inputs are used to cancel out the steady state error of the system. Accordingly, the control effort is evaluated based on a different set of errors. As a result, more effective control actions are implemented to the system. The results show that, the performance specifications of the systems are remarkably enhanced. The enhancement results obtained, include, much limited bounds of the control effort, smaller delay, enhanced transient response, and zero steady state error.

A Method for Turning a Single Low-Cost Cube into a Reference Target for Point Cloud Registration

Target-based point cloud registration methods are still widely used by many laser scanning professionals due to their direct and manipulable nature. However, placing and moving multiple targets such as spheres for registration is a time-consuming and tactical process. When the number of scans gets large, the time and labor costs will accumulate to a high level. In this paper, we propose a flexible registration method that requires the installation of only a low-cost cubical target: a die-like object. The method includes virtual coordinate system construction and two error compensation techniques, in which the non-orthogonality of the scanned facets, along with the unknown sizes of the dice are estimated based on projection geometry and cubical constraints so that three pairs of conjugate points can be accurately identified along the axes of the constructed coordinate systems for the registration. No scan overlap of the facet is needed. Two different low-cost dice (with a volume of 0.125 m3 and 0.027 m3) were used for verifying the proposed method, which shows that the proposed method delivers registration accuracy (with an RMSE discrepancy of less than 0.5 mm for check planes) comparable to the traditional sphere- based method using four to six spherical targets spanning the scene. Therefore, the proposed method is particularly useful for registering point clouds in harsh scanning environments with limited target-setting space and high chances of target interruption.

Automatic phase error compensation of rotary traveling wave oscillator: Analysis and design

Automatic phase error compensation of rotary traveling wave oscillator: Analysis and design

Robust Control Based on Modeling Error Compensation of Microalgae Anaerobic Digestion

Microalgae are used to produce renewable biofuels (biodiesel, bioethanol, biogas, and biohydrogen) and high-value-added products, as well as in bioremediation and CO2 sequestration tasks. In the case of anaerobic digestion of microalgae, biogas can be produced from mainly proteins and carbohydrates. Anaerobic digestion is a complex process that involves several stages and is susceptible to operational instability due to various factors. Robust controllers with simple structure and design are necessary for practical implementation purposes and to achieve a proper process operation despite process variabilities, uncertainties, and complex interactions. This paper presents the application of a control design based on the modeling error compensation technique for the anaerobic digestion of microalgae. The control design departs from a low-order input–output model by enhancement with uncertainty estimation. The results show that achieving desired organic pollution levels and methanogenic biomass concentrations as well as minimizing the effect of external perturbations on a benchmark case study of the anaerobic digestion of microalgae is possible with the proposed control design.

Ultra-precision raster grinding biconical optics with a novel profile error compensation technique based on on-machine measurement and wavelet decomposition

Abstract Biconical optics with excellent profile accuracy and bright surface finish are increasingly applied in the fields of aviation, aerospace, biology, consumer electronics, etc. However, the extreme demand of micron/sub-micron scaled profile accuracy of the biconical optics poses a great challenge for the manufacturing process. In this study, a novel compensation strategy was developed based on the on-machine non-contact laser displacement sensor and wavelet decomposition technique for depressing the final profile error of biconical optics machined by raster grinding. Firstly, a profile error evaluation model was established to restructure the error surface measured by the laser sensor, and the low-frequency profile error was separated successfully from the reconstructed errors using the proposed technology. Secondly, the momentous error sources that affect the profile accuracy were identified and analyzed, and a wheel-error model was established based on the correspondence between the error sources and the profile errors, which is then applied for the wheel path compensation. Finally, the compensation experiments were undertaken. The profile errors along the workpiece length (220 mm) and workpiece height (105 mm) decreased from 15.425 μm to 1.678 μm and 18.6 μm to 1.6948 μm, respectively. The PV-values of the machined surface with profile error compensation reduced from 21.6 μm to 1.5486 μm in a 220m × 105 mm measurement area. This demonstrates the effectiveness of the proposed profile error compensation methods for the biconical surface.

Design and Verification of a Charge Pump in Local Oscillator for 5G Applications

A charge pump (CP) that has low current mismatch to reduce the locking time of the Phase-Locked Loop (PLL) is proposed. The design is promising in 5G applications with the capabilities of fast settling and low power consumption. In this design, a charge pump architecture consists of an operational power amplifier (OPA), switches, three D flip-flops (DFFs) and passive devices. A phase error compensation technique is introduced in the charge pump to reduce the locking time. The current mismatch, which is mainly due to the leakage current, is below 1% for a large output voltage headroom of 84% of the supply voltage. An 18.4% reduction in the settling time is realized by the proposed design.