To address the enhanced matrix effects and intensified nonlinear spectral responses caused by the difficulty of grinding large-particle coal in industrial settings,this study proposes a hybrid PLS-AE-RR predictive model based on the fusion of near-infrared spectroscopy(NIRS)and X-ray fluorescence(XRF)spectra,aimed at improving the accuracy of on-line calorific-value analysis.The method implements a three-stage hybrid framework--linear baseline+nonlinear feature extraction+residual correction--where partial least squares regression(PLS)first models the global linear relationship between the fused spectra and calorific value;an autoencoder(AE)then extracts low-dimensional nonlinear representations that PLS cannot capture;and finally ridge regression(RR)fits and corrects the nonlinear residuals.Exper-imental validation using 153 blended coal samples from power plants demonstrates breakthrough perfor-mance in calorific value prediction for large-particle-size coal.On the test set,determination coefficients(R²)for lignite and bituminous coal reached 0.974 and 0.938,respectively,with mean absolute errors of 0.233 MJ/kg and 0.216 MJ/kg.The proposed method significantly outperforms standalone PLS and al-ternative nonlinear correction models,confirming the generalization advantage of ridge regression in residu-al fitting.Consequently,this achievement provides a grinding-free,high-precision online analysis solution for raw coal calorific value in coal-fired power plants,offering critical technical support for refined fuel man-agement and operational optimization.
The workflow begins with approximate orthorectification of aerial images using coarse position-ing results and flight parameters,followed by extraction of the corresponding satellite image regions.RepVGG is employed to extract coarse image features,and initial correspondences are established via nearest-neighbor matching.Candidate pairs are then filtered using MiHo clustering and normalized cross-correlation(NCC).The refined correspondences are further enhanced by a Transformer module to achieve precise alignment.Based on the resulting high-precision matches,an angular error correction ma-trix is constructed,and iterative refinement is applied to effectively compensate for systematic errors.Ex-perimental results indicate that the proposed method substantially improves positioning accuracy relative to conventional approaches,achieving an approximately 70%enhancement in representative scenarios;even at a slant range of 90 km,the positioning error remains approximately 120 m.By leveraging image match-ing under challenging viewing geometries,the proposed passive localization method provides a novel solu-tion to limitations of conventional algorithms.A two-step matching strategy integrating Transformer-based feature enhancement with MiHo clustering-based filtering is introduced,effectively mitigating the ac-curacy degradation of traditional passive localization under high-altitude,large-oblique viewing conditions in the presence of small angular errors.
A commercially available transparent phone case was used as the substrate,and an Ag@Cu mi-cro-/nano-composite antibacterial coating was fabricated on its surface via laser-induced backward transfer(LIBT).The results indicated a positive correlation between laser power and the elemental content of the microstructured coating,with the mass ratios of Ag and Cu increasing as laser power increased.This ap-proach enables efficient fabrication under ambient atmospheric conditions with a simple and cost-effective process.The resulting microstructured coating exhibited pronounced antibacterial activity against both Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli.At laser powers of≥16 W,the antibacterial rate exceeded 99.99%,and the increased copper mass ratio further enhanced antibacterial efficacy.These findings address key limitations of conventional technologies by enabling high-precision construction of micro-/nano-structures on transparent substrates.Moreover,the processing parameters are precisely controllable,supporting scalable manufacturing and offering a general strategy for functional-izing the surfaces of other transparent organic materials.Overall,a practical route for producing antibacte-rial phone cases is established,providing methodological guidance for the design and fabrication of ad-vanced antibacterial surfaces and addressing bacterial contamination and insufficient antibacterial perfor-mance in mobile phone casings.
To improve the 3D visualization effect and autostereoscopic display performance of medical im-ages,this paper proposed a light field display method for medical images based on virtual light field acquisi-tion.First,based on medical tomographic image data,preprocessing algorithms were adopted to process the original image data.Combined with surface reconstruction and the improved Quadric Error Metrics(QEM)simplification algorithm,a lightweight 3D medical model was constructed while its key structural features were preserved.Then,aiming at the limitations of traditional light field acquisition methods,a virtual camera array construction strategy based on computer graphics was further designed.It generated high-quality virtual light field content without relying on physical optical equipment.Finally,the light field acquisition scene was built for the simplified 3D model using multi-view rendering technology.It opti-mized the acquisition efficiency and spatial resolution of light field images.Experimental results show that the rendering overhead of the medical model is reduced by 90.16%.And the geometric accuracy of the model is only lost by 4.06%.The virtual light field acquisition system achieved rendering efficiencies of 9.83 frames per second(FPS)and 9.57 FPS on the two optical experimental platforms,respectively,with a substantial enhancement in the generation efficiency of elemental images,thereby largely fulfilling the real-time acquisition criteria.The proposed method significantly reduces the model complexity while ensuring the geometric accuracy of the medical model,and effectively improves the quality and real-time performance of virtual light field display.
To address the issues of complex crack morphologies,environmental interference,and the im-balance between detection accuracy and model lightweight requirements in road surface inspection,this pa-per proposed a lightweight road crack detection method with adaptive feature extraction.First,a Crack Ef-ficient Attention(CEA)module was designed based on the slender shape and large span characteristics of cracks,compressing feature dimensions to capture long-distance spatial dependencies.Second,a Dynamic Sampling Feature Pyramid Network(DSFPN)was constructed for adaptive sampling and target feature extraction,enhancing representation capability for heterogeneous crack features.Third,the HGNet_GS lightweight backbone network was improved,and a CEA Group Head(CGHead)was proposed,signifi-cantly reducing computational redundancy;the PIoU(Powerful IoU)loss function was adopted to solve anchor box expansion problems and improve convergence speed for small models.Additionally,a civilian road defect dataset containing 2 985 images under various lighting conditions was established to validate model generalization.Experimental results show that compared with the baseline YOLOv8n model,the proposed method reduces parameters and computational cost by 50%and 52%,respectively;on the self-built dataset,mAP50 and mAP95 increase by 5.4%and 4.1%;on the public RDD2022 dataset,these metrics improve by 2.1%and 1.5%.The model has been deployed on edge devices and verified through engineering tests,demonstrating its capability to meet practical requirements for lightweight road crack de-tection and providing a technical solution for automated road maintenance systems.
Deterministic ion-beam figuring of high-precision optical surfaces requires stable and accurate-ly controllable removal functions.To improve in-process control of the ion-beam removal function and to establish a variable removal-function compensation model for fine-beam-diameter ion beams,a sys-tematic framework was developed for investigating,compensating,and optimizing removal-function variability during machining.First,the practical instability of the removal function was analyzed theoret-ically.Subsequently,the governing factors were derived and classified into direct effects(thermal accu-mulation and energy distribution)and indirect effects(dwell time and lateral velocity).Dynamic remov-al-function experiments were then performed to validate the influence of dwell time on the removal rate,and tests using two beam diameters confirmed the generality of the observed behavior.Finally,a com-pensation strategy and machining guidelines were proposed based on the effect of lateral velocity on the removal rate.The results demonstrate that regulating dwell time and lateral velocity can significantly en-hance the convergence rate in fine-beam-diameter machining of high-precision optical surfaces.In sub-nanometer machining validation,a 0.332 nm RMS figure error was achieved on a 100 mm ULE flat mir-ror,satisfying practical requirements for stability,reliability,high precision,and controllability of fine-beam-diameter ion-beam processing.
Piezoelectric actuators(PEA)are widely used for micro-nano-positioning and precision manu-facturing due to their high resolution and rapid response.Inherent hysteresis nonlinearity affects control performance and restricts high-accuracy applications.To overcome the limitations of the classical Prandtl-Ishlinskii(P-I)model in representing complex nonlinear hysteresis phenomena,a multilayer neural net-work-enhanced P-I modeling approach was proposed.The method used a neural network to dynamically map the weights of Play operators while ensuring that the model remained invertible and physically inter-pretable.Bayesian regularization was adopted during training to improve the ability to fit nonlinear systems and enhance generalization.Based on the improved model,an inverse-model-based feedforward controller was designed and validated in real-time experiments.Experimental results show that the proposed feedfor-ward compensation reduces the normalized RMSE to 0.65%,0.76%,and 1.82%under triangular,sinu-soidal,and hybrid inputs,significantly outperforming the classical and its polynomial variants.The meth-od exhibits strong robustness across diverse input conditions and demonstrates good engineering applicabili-ty in complex hysteresis modeling and high-precision control.
Regarding the multi-degree-of-freedom,macro-stroke,and high-precision motion requirements in micro-manipulation and micro-assembly fields,a two-degree-of-freedom cross-scale parallel decoupled motion platform with piezoelectric stick-slip actuation was proposed.Macro fiber composites were used to actuate compliant mechanisms to design an integrated drive-structure arch-shaped driving unit,achieving nanometer-level motion resolution,enhancing single-step output displacement,and enabling two-dimen-sional planar motion decoupling.Subsequently,stick-slip driving principles were utilized to achieve macro-stroke motion,while universal bearings and adjustable support were employed to enhance load-bearing ca-pacity.A theoretical model of the platform was established using the finite element method,and simula-tions were conducted to analyze its output displacement and natural frequency.Finally,an experimental platform was constructed to test the relevant performance.Experimental results show that during continu-ous stRegarding the multi-degree-of-freedom,macro-stroke,and high-precision motion requirements in micro-manipulation and micro-assembly fields,a two-degree-of-freedom cross-scale parallel decoupled mo-tion platform with piezoelectric stick-slip actuation is proposed.Macro fiber composites are used to actuate compliant mechanisms to design an integrated drive-structure arch-shaped driving unit,achieving nanome-ter-level motion resolution,enhancing single-step output displacement,and enabling two-dimensional pla-nar motion decoupling.Subsequently,stick-slip driving principles are utilized to achieve macro-stroke mo-tion,while universal bearings and adjustable support are employed to enhance load-bearing capacity.A theoretical model of the platform is established using the finite element method,and simulations are con-ducted to analyze its output displacement and natural frequency.Finally,an experimental platform was constructed to test the relevant performance.ep motion,the maximum single-step displacements of the piezoelectric stick-slip motion platform along the x and y axes are 249.6 μm and 237.3 μm,respectively,with a motion range of 16.10 mm×16.08 mm.Even under a vertical load of 30 N,the stick-slip motion platform still achieves a single-step output displacement of 16 μm.Additionally,the translational displace-ment resolutions are 6.3 nm and 6.8 nm during single-step precision motion,respectively.Therefore,the designed piezoelectric stick-slip motion platform can meet the multi-dimensional,cross-scale micro-nano motion requirements.
To enhance the control precision of aerial dynamic optical imaging systems,this study address-es the high-precision control problem of Voice Coil Motor-Driven Mirrors(VCMM)by proposing an inte-grated control strategy based on an adaptive sliding mode finite-time control.This strategy enables precise command tracking under conditions of external disturbances and model uncertainties.First,a generalized form of the system dynamics model was established based on the electromechanical characteristics of the VCMM.Second,a nonlinear proportional-integral-derivative type sliding surface was constructed to im-prove the convergence speed of the control system and suppress steady-state errors.Based on this,follow-ing a hierarchical anti-disturbance framework,feedback control terms related to model parameters and er-rors,sliding mode switching control terms,and adaptive control terms were designed.The finite-time con-vergence characteristics of the closed-loop system were rigorously demonstrated using Lyapunov stability theory.Finally,the effectiveness of the proposed composite control strategy was validated through com-parative experiments.Experimental results showed that under a sinusoidal command with an amplitude of 180 arcseconds and a frequency of 1 Hz,and in the presence of periodic bounded disturbances,the system achieved tracking errors with root mean square and peak-to-peak values of only 0.28 arcseconds and 4.04 arcseconds,respectively,significantly outperforming conventional sliding mode control.The proposed control algorithm not only maintains excellent tracking performance but also demonstrates superior distur-bance suppression capabilities.This study provides an effective solution for addressing disturbance rejec-tion and tracking control in high-precision aerial optoelectronic imaging systems.
The inherent hysteresis of piezoelectric fast steering mirrors(PFSMs)severely limits control accuracy in precision positioning systems.To address this limitation,the performance of common enve-lope functions is systematically compared in terms of computational complexity,inversion requirements,and error sources.Based on a comprehensive evaluation,an asymmetric linear envelope function is select-ed,and a rate-dependent generalized Prandtl-Ishlinskii model with an asymmetric linear envelope function(LRGPI)is developed.To mitigate rate-dependent hysteresis,a derivative term is incorporated to extend the model's applicable frequency range.The inverse LRGPI model is subsequently formulated and imple-mented as a feedforward compensator to evaluate hysteresis suppression.Furthermore,a composite con-trol strategy integrating inverse-model feedforward compensation is designed to attenuate external distur-bances.Simulation results indicate that,relative to the inverse models of the tanh envelope-based rate-de-pendent generalized Prandtl-Ishlinskii model(TRGPI)and the cubic envelope-based rate-dependent gen-eralized Prandtl-Ishlinskii model(CRGPI),the LRGPI inverse-model feedforward increases the hystere-sis-compensation bandwidth by 5.78%and 28.69%,respectively.Comparative experiments further dem-onstrate that the RMSE achieved by LRGPI inverse-model feedforward control is reduced by 62.7%,23.2%,and 26.4%compared with the PI inverse model,TRGPI,and CRGPI inverse models,respec-tively.These results demonstrate the superior effectiveness and robustness of the proposed LRGPI model for compensating PFSM hysteresis.
To address the high computational complexity,limited feature robustness,and constrained clas-sifier performance of conventional object detection methods in ore particle size detection,a few-shot object detection approach was proposed to reduce annotation cost and improve generalization under data-scarce conditions.The proposed method was built upon the CenterNet2 framework and employed a lightweight VoVNet as the backbone to ensure detection efficiency.A parallel dual-attention feature fusion module was designed as the core component.Specifically,a channel cross-attention module was introduced to re-calibrate channel-wise feature responses,while a spatial group-attention module emphasized discriminative target regions.The coordinated operation of the two modules enhanced the fusion of task-relevant features and provided effective guidance for query image detection in few-shot scenarios.Experimental results on an ore dataset show that the proposed model achieved an average precision(AP)of 55.2%,with AP50 and AP75 reaching 78.5%and 66.9%,respectively.The inference speed reached 57 frames per second(FPS),while the attention module required only 16.1 M parameters,indicating a favorable trade-off be-tween accuracy and efficiency.Experimental results demonstrate that the proposed method effectively en-hances the perception performance of few-shot ore particle size detection.Moreover,it possesses high po-tential for edge deployment,providing a reliable technical solution for real-time detection challenges in smart mines under computation-constrained conditions.
Accurate assessment and correction of on-orbit pointing errors and tangent height deviations of limb sounders are essential for achieving high vertical accuracy in global trace retrievals.For the newly launched Ozone Monitoring Suite-Limb(OMS-L)onboard Fengyun-3F,the geometric pointing model of the scanning mirror was established based on the precisely measured instrument coordinate system.The tangent height calculation model was constructed using an equidistant virtual ellipsoid.Eight configuration parameter modes were designed to analyze the influence of the earth model,orbital and attitude informa-tion,installation parameters,and their combined effects on the theoretically designed tangent heights.During on-orbit testing,the systematic tangent height deviation was identified by knee-point method.To correct this deviation,the pitch installation parameters were adjusted,and the pointing stability of the in-strument was statistically analyzed over a period of 12 months.The results show that the tangent height correction accuracy is better than 0.4 km,and the annual inter-annual variation of the instrument vertical(along-track)pointing is less than 0.01°.For cross-track pointing accuracy,image matching was per-formed using reference images acquired from the same platform and spectral band of the earth observation instrument.The results show that the cross-track pointing deviation of OMS-L reach 0.1°.The on-orbit pointing accuracy of OMS-L met the requirements for trace gas inversion and retrieval.
Flexible photodetectors show considerable potential for wearable electronics,curved imaging,and intelligent sensing;however,their performance is frequently constrained by weak interfacial coupling between micro/nanoscale photoactive structures and flexible substrates,leading to high dark current and el-evated power consumption.Here,a performance-enhancement strategy exploiting the piezophototronic ef-fect is proposed.A dual-component self-assembled ZnO@(Cu(NH3))(CN)multilayer nanofiber architec-ture was fabricated via electrohydrodynamic direct writing,in which ZnO functions as the primary photoac-tive fiber and(Cu(NH3))(CN)serves as an auxiliary modulation layer.This stacked configuration mark-edly strengthens interfacial coupling stability and,through piezophototronic modulation at the stacking in-terfaces,introduces asymmetric barriers and built-in electric fields that effectively suppress thermally excit-ed carrier transport.As a result,the dark current is reduced to 1.12×10-7 A,substantially decreasing static power consumption.By adjusting the number of stacked layers(5-25),the threshold voltage can be tuned from 6 to 20 V,enabling programmable logic control.Under 254 nm ultraviolet illumination,a re-sponsivity of 13.3 A/W is achieved,with response and recovery times of 11 ms and 9 ms,respectively,demonstrating excellent photoelectric detection performance.These results indicate that the orthogonally stacked ZnO and(Cu(NH3))(CN)nanofiber architecture enables superior local electric-field regulation and enhanced photoelectric conversion efficiency,offering strong promise for low-power,high-response flexible photodetectors.
To address the constraints of hardware cost and onboard data storage in high-resolution aero-space CMOS cameras for small satellites,a full-pipeline FPGA-based implementation of the JPEG-LS im-age compression algorithm is proposed.A multicore real-time compression imaging system is integrated on a single FPGA using a parallel grouping architecture.First,multichannel high-speed image streams from CMOS detectors are received by the FPGA.Second,the JPEG-LS algorithm is realized using an eleven-stage pipeline,and the encoding-parameter calculation and context-update modules are structurally optimized to reduce the critical path.Finally,multiple JPEG-LS compression kernels are employed to group and compress the multichannel data in parallel.Experimental results indicate that,in the implement-ed system,the optimized JPEG-LS core achieves a maximum operating frequency of 46 MHz.With the compression parameter near set to 1,a near-lossless compression ratio exceeding 4 is obtained,and the peak signal-to-noise ratio(PSNR)of the decompressed images is approximately 50 dB.These results sat-isfy the compression-rate and image-quality requirements for remote-sensing imagery,providing a practical reference for designing high-resolution spaceborne CMOS cameras with integrated image compression.
To address the color deviation and detail blur of underwater images caused by scattering and at-tenuation when light propagated in the underwater environment,an improved U-Net global feature fusion underwater image enhancement network was proposed.Firstly,a multi-residual convolution module was designed in the encoder and decoder to fuse the feature information hierarchically to reduce the loss of de-tail information.Secondly,the channel attention module was introduced into the decoder to weight the channels to alleviate the problem of different degrees of channel degradation.Finally,a convolution-per-muted self-attention module was designed in the decoder to fuse the global information and promote the network-guided image reconstruction.The proposed method was tested on UIEB dataset,and finally achieved 23.42,0.900 5 and 0.138 5 on PSNR,SSIM and LPIPS,respectively.The results on LSUI dataset were 29.35,0.938 2 and 0.088 0 on PSNR,SSIM and LPIPS,respectively.Compared with other commonly used underwater image enhancement methods on several public underwater image datas-ets,the experimental results show that the proposed method has good effect in restoring color deviation and reducing detail blur,which proves its effectiveness and feasibility.
To satisfy augmented reality(AR)optical waveguide requirements for a large field of view(FOV),thin and lightweight form factor,and high immersion,a mass-producible thin-lightweight trans-missive head-mounted display(HMD)optical system based on an arrayed geometric thin-film waveguide architecture was designed and implemented.The system comprises an eyepiece,an arrayed waveguide module,and an illumination module.The arrayed waveguide employs an array of semi-transparent,semi-reflective films with customized angle-selective coatings as the optical combiner,enabling pupil expansion.A dual-waveplate polarization-mixing scheme was introduced,improving display uniformity from 59.66%to 61.12%under single-polarized illumination and to 76.61%in practical measurements.Through com-prehensive optical simulation and system-level optimization,and supported by a mature domestic optical manufacturing chain-including precision cutting,grinding and polishing,vacuum deposition of complex multilayer films,and high-precision bonding-together with an added waveplate lamination process,key technical barriers limiting the mass production of arrayed waveguides were overcome.A prototype was fabricated,and mass production was achieved.The proposed approach resolves the longstanding trade-off between optical performance and manufacturability in AR HMDs,supporting both consumer and industrial applications.
High-precision positioning is required for lunar polar landing,and crater-based visual navigation can be used to estimate the lander pose.However,this approach is limited by an insufficiently character-ized mechanism for pose estimation error propagation and by the lack of practical engineering parameters.To address these issues,pose error modeling for crater visual navigation is investigated.A pose error mod-el based on weighted least squares is proposed to quantify pose errors under the combined effects of multi-ple factors.First,traceability analysis and baseline modeling of pose errors are performed according to the pose estimation principle of crater visual navigation.Second,a pose error model is formulated by minimiz-ing the reprojection error.Finally,weighted least squares is applied to obtain quantitative pose error esti-mates.Using DEM and DOM data from the lunar polar region,crater visual navigation for a lunar lander is simulated,and Monte Carlo-based experiments are conducted to evaluate the effects of different error sources and feature parameters on pose accuracy.When the pixel detection error is 5 pixels and 15 craters are used,the estimated translation error is below 95 m.The developed model enables quantitative pose er-ror estimation under multiple contributing factors,and the proposed engineering parameter scheme satis-fies the 100 m-level navigation accuracy requirement for lunar polar landing.This work provides a theoreti-cal basis for the design of crater-based navigation schemes.
Chitosan,as a bio-based material,combines environmental friendliness with excellent moisture adsorption capacity.However,its inherent high-humidity swelling characteristics often lead to issues such as,slow response and low long-term reliability in humidity sensors.To address these problems,a humidi-ty sensor based on chitosan-molybdenum disulfide composite material was proposed in this study,aiming to achieve high sensitivity and fast response.By incorporating two-dimensional molybdenum disulfide nanosheets into the chitosan matrix,a chitosan-MoS₂ composite humidity-sensitive film with a cross-linked network was constructed.Characterization and performance test results show that molybdenum disulfide nanosheets not only form a cross-linked network with chitosan through hydrogen bonding,but also con-struct a physical barrier layer,which effectively suppresses the swelling of the material under high humidi-ty conditions,and enhances the water molecule adsorption capacity and interfacial polarization effect of the film.The prepared chitosan-MoS2 sensor exhibits a wide operating humidity range(7%RH-95%RH),high sensitivity(14 200 pF/%RH),short response/recovery time(15/25 s),good repeatability(5 rela-tive standard deviation 2.08%over 5 cycles)and long-time stability(no attenuation over 120 h).Further-more,the sensor demonstrates potential application value in respiratory pattern recognition and non-con-tact human-computer interaction.This study provides an effective design and fabrication strategy for the development of high-performance and stable humidity sensors.
Optical surgical navigation systems used in complex minimally invasive procedures are vulnera-ble to multisource disturbances,including surgeons'physiological tremor,device vibration,and imaging noise.Such disturbances can induce localization jitter and trajectory discontinuities.To mitigate insuffi-cient system robustness caused by the combined effects of disturbance-induced noise and system-model un-certainty,an adaptive strong-tracking-filtering-based method is proposed for surgical instrument localiza-tion and guidance,thereby enhancing the stability and reliability of optical surgical navigation.In the posi-tion domain,a strong tracking Kalman filter with error-statistics-based adaptive adjustment of the noise co-variance matrices is employed to improve suppression of abrupt noise and drift.In the attitude domain,a quaternion unscented Kalman filter is adopted to avoid linearization errors while preserving quaternion nor-malization.To further enhance smoothing performance,moving-average preprocessing is applied to the position input to integrate low-frequency stability with high-frequency disturbance attenuation.Datasets from eight distinct scenarios were collected for experimental validation,and the proposed method was com-paratively evaluated against existing approaches using seven performance metrics.The results indicate that the proposed method achieves superior overall performance.For attitude tracking,the angular root-mean-square error is reduced by 50%-79%relative to the reference methods.For position tracking,the overall trend residual is further reduced by 5%-20%compared with the standard Kalman filter,yielding an im-proved balance between high-frequency noise suppression and dynamic response stability.These results demonstrate significant gains in micro-disturbance suppression,attitude stability,and noise adaptability,providing a theoretical basis for high-precision medical navigation.
To meet the comprehensive requirements of high force density and high-precision control for a medium-stroke micro-nano precision positioning stage,a compliant precision positioning stage based on re-luctance actuators was designed and analyzed,with nonlinear hysteresis modeling and trajectory tracking control implemented.First,by analyzing the equivalent magnetic circuit of the reluctance actuator and its drive force characteristics under different air gaps,combined with the stiffness model of the flexure mecha-nism,the stage design parameters and the suitable air gap size for stage operation were determined.Subse-quently,an experimental system was set up,and a feedforward compensation strategy incorporating a ra-tional function and a Prandtl-Ishlinskii hysteresis inverse model was constructed to achieve nonlinear com-pensation for the reluctance actuator.Finally,a feedback control method comprising proportional-integral control and a notch filter was utilized to conduct trajectory tracking control experiments.Experimental re-sults demonstrate that the constructed hysteresis inverse model compensation and control method signifi-cantly enhances the stage's control accuracy.After nonlinear compensation,the root mean square errors for tracking two different triangular wave signals were reduced by 69.2%and 63.68%,respectively,vali-dating the feasibility and effectiveness of the designed compliant precision positioning stage using reluc-tance actuation in micro-nano positioning applications.
