A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which ca...A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which can accurately describe the strain and stress states in IF.Based on strain analysis,the model can predict the material thickness distribution and neck height after IF.By considering contact area,strain characteristics,material thickness changes,and friction,the model can predict specific moments and corresponding values of maximum axial forming force and maximum horizontal forming force during IF.In addition,an IF experiment involving different tool diameters,flanging diameters,and opening hole diameters is conducted.On the basis of the experimental strain paths,the strain characteristics of different deformation zones are studied,and the stable strain ratio is quantitatively described through two dimensionless parameters:relative tool diameter and relative hole diameter.Then,the changing of material thickness and forming force in IF,and the variation of minimum material thickness,neck height,maximum axial forming force,and maximum horizontal forming force with flanging parameters are studied,and the reliability of the analytical model is verified in this process.Finally,the influence of the horizontal forming force on the tool design and the fluctuation of the forming force are explained.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexit...We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexity theory. By incorporating general relativistic effects into complexity theory through a gravitational correction factor, we prove that problems can transition between complexity classes depending on the observer’s reference frame and local gravitational environment. This insight emerges from recognizing that the definition of polynomial time implicitly assumes a universal time metric, an assumption that breaks down in curved spacetime due to gravitational time dilation. We demonstrate the existence of gravitational phase transitions in problem complexity, where an NP-complete problem in one reference frame becomes polynomially solvable in another frame experiencing extreme gravitational time dilation. Through rigorous mathematical formulation, we establish a gravitationally modified complexity theory that extends classical complexity classes to incorporate observer-dependent effects, leading to a complete framework for understanding how computational complexity transforms across different spacetime reference frames. This finding parallels other self-referential insights in mathematics and physics, such as Gödel’s incompleteness theorems and Einstein’s relativity, suggesting a deeper connection between computation, gravitation, and the nature of mathematical truth.展开更多
The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool...The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.展开更多
The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned...The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned only for pure states,has limited applicability in realistic scenarios where mixed states are common.To address this limitation,we generalize the defnition of the QGT to mixed states using the purifcation bundle and the covariant derivative.Notably,our proposed defnition reduces to the traditional QGT when mixed states approach pure states.In our framework,the real and imaginary parts of this generalized QGT correspond to the Bures metric and the mean gauge curvature,respectively,endowing it with a broad range of potential applications.Additionally,using our proposed mixed-state QGT,we derive the geodesic equation applicable to mixed states.This work establishes a unifed framework for the geometric analysis of both pure and mixed states,thereby deepening our understanding of the geometric properties of quantum states.展开更多
Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitation...Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system parameters.Consequently, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS theories.The paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded conditions.The paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.展开更多
In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Usin...In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Using the coupling method,we obtain the existence of a full absorbing set on which continuous time Markov processes are f-geometric ergodic.展开更多
Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system rob...Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.展开更多
When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is...When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.展开更多
The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment ene...The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment energy of Co_(2)Ge_(10)^(-)was measured to be 2.86±0.08 eV.The lowest-energy isomer of Co_(2)Ge_(10)^(-)is in a doublet state and has a cage-like structure with Cs symmetry,which can be constructed by a tetragonal bipyramid on top of a pentagonal bipyramid and these two bipyramid structures share a common Co atom.The most stable structure of neutral Co_(2)Ge_(10)resembles its anionic counterpart and it is in a triplet state.The natural population analysis showed that the inner Co atom of both the anionic and neutral Co_(2)Ge_(10)acquires negative charge from the neighboring Ge atoms.The outer Co atom has a larger spin moment than the inner Co atom,indicating that the magnetic moments of Co_(2)Ge_(10)^(-/0)are mainly contributed by the outer Co atom.Analyses of the density of states and molecular orbitals indicated that there are a few highly delocalized molecular orbitals in Co_(2)Ge_(10)^(-),which are mainly contributed by Ge 4s atomic orbitals.展开更多
In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values ...In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values in certain specific Banach spaces.Next,we investigate the relationships between this new constant and other classical constants.Specifically,we establish an inequality relationship between it and the J(X)constant,as well as an identity relationship between it and theρX(t)constant.Furthermore,we characterize some geometric properties of Banach spaces by means of this new constant.Finally,by restricting the above-mentioned constant to the unit sphere,we introduce another new constant,calculate its upper and lower bounds,and present a relevant example.展开更多
In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing e...In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.展开更多
This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accur...This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accuracy of the solution are studied using two columns,two braced frames,and one unbraced frame.Discussion is provided when the new geometric stiffness matrix can be used to improve the buckling load analysis results and when it may provide only nominal additional benefit.展开更多
This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorit...This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.展开更多
In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce...In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.展开更多
Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under bo...Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under both weak and strong qubit-reservoir coupling regimes.The multiqubit system is connected with either a common bosonic reservoir(CBR)or multiple independent bosonic reservoirs(IBRs).In the CBR case,our findings indicate that both QD and GQD can be strengthened by increasing the number of qubits in the multiqubit system.Furthermore,we study the steady state QD and GQD in the strong coupling regime,and find that the stable value in the long-time limit is determined exclusively by the number of qubits.The evolution period of QD and GQD gets longer as the dipole–dipole interaction(DDI)strength increases,which helps prolong the correlation time and thus preserves the quantum correlation under the weak coupling regime.Further analysis reveals notable differences between the CBR and IBRs scenarios.In the IBRs case,the decay of QD and GQD becomes slower compared to the CBR case,with both measures tending to zero at a reduced rate.Moreover,GQD consistently exhibits lower values than QD in both scenarios.These findings provide valuable insights into the selection of appropriate correlation measurement techniques for quantifying quantum correlations.展开更多
In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and de...In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.展开更多
This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial...This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.展开更多
Geometric phase gates have attracted considerable attention due to their intrinsic robustness against certain types of noise.Significant progress has been achieved in implementing geometric phase gates using microwave...Geometric phase gates have attracted considerable attention due to their intrinsic robustness against certain types of noise.Significant progress has been achieved in implementing geometric phase gates using microwave control in siliconbased electron spin systems.In this work,we propose an alternative geometric phase gate protocol that differs fundamentally from microwave driving approaches by leveraging square-wave control of rapidly switchable micromagnets driven by spin-orbit torque(SOT)to achieve fast and precise magnetic field modulation.By employing square-wave currents to control magnetization switching,our approach relaxes the requirements on waveform precision while significantly suppressing crosstalk.Moreover,our scheme inherently preserves trajectory closure at the end of each operation,effectively mitigating noise-induced path deviation and enhancing gate robustness even under strong noise conditions,thereby offering a promising pathway toward efficient and reliable quantum operations in large-scale qubit arrays.展开更多
基金supported in part by financial support from the National Key R&D Program of China(No.2023YFB3407003)the National Natural Science Foundation of China(No.52375378).
文摘A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which can accurately describe the strain and stress states in IF.Based on strain analysis,the model can predict the material thickness distribution and neck height after IF.By considering contact area,strain characteristics,material thickness changes,and friction,the model can predict specific moments and corresponding values of maximum axial forming force and maximum horizontal forming force during IF.In addition,an IF experiment involving different tool diameters,flanging diameters,and opening hole diameters is conducted.On the basis of the experimental strain paths,the strain characteristics of different deformation zones are studied,and the stable strain ratio is quantitatively described through two dimensionless parameters:relative tool diameter and relative hole diameter.Then,the changing of material thickness and forming force in IF,and the variation of minimum material thickness,neck height,maximum axial forming force,and maximum horizontal forming force with flanging parameters are studied,and the reliability of the analytical model is verified in this process.Finally,the influence of the horizontal forming force on the tool design and the fluctuation of the forming force are explained.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexity theory. By incorporating general relativistic effects into complexity theory through a gravitational correction factor, we prove that problems can transition between complexity classes depending on the observer’s reference frame and local gravitational environment. This insight emerges from recognizing that the definition of polynomial time implicitly assumes a universal time metric, an assumption that breaks down in curved spacetime due to gravitational time dilation. We demonstrate the existence of gravitational phase transitions in problem complexity, where an NP-complete problem in one reference frame becomes polynomially solvable in another frame experiencing extreme gravitational time dilation. Through rigorous mathematical formulation, we establish a gravitationally modified complexity theory that extends classical complexity classes to incorporate observer-dependent effects, leading to a complete framework for understanding how computational complexity transforms across different spacetime reference frames. This finding parallels other self-referential insights in mathematics and physics, such as Gödel’s incompleteness theorems and Einstein’s relativity, suggesting a deeper connection between computation, gravitation, and the nature of mathematical truth.
基金Supported by the National Natural Science Foundation of China(Grant Nos.52375448,52275440).
文摘The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.
基金supported by the National Natural Science Foundation of China(Grant Nos.12347104,U24A2017,12461160276,and 12175075)the National Key Research and Development Program of China(Grant No.2023YFC2205802)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant Nos.BK20243060 and BK20233001)in part by the State Key Laboratory of Advanced Optical Communication Systems and Networks,China。
文摘The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned only for pure states,has limited applicability in realistic scenarios where mixed states are common.To address this limitation,we generalize the defnition of the QGT to mixed states using the purifcation bundle and the covariant derivative.Notably,our proposed defnition reduces to the traditional QGT when mixed states approach pure states.In our framework,the real and imaginary parts of this generalized QGT correspond to the Bures metric and the mean gauge curvature,respectively,endowing it with a broad range of potential applications.Additionally,using our proposed mixed-state QGT,we derive the geodesic equation applicable to mixed states.This work establishes a unifed framework for the geometric analysis of both pure and mixed states,thereby deepening our understanding of the geometric properties of quantum states.
基金supported by the National Natural Science Foundation of China(62133008,62303273,62188101,62373226,62473173)Young Taishan Scholars Program of Shandong Province of China(tsqn202408206)+2 种基金a Project of Shandong Province Higher Educational Youth and Innovation Talent Introduction and Education Programthe Natural Science Foundation of Shandong Province,China(ZR2023QF072)China Postdoctoral Science Foundation(2022M721932)
文摘Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system parameters.Consequently, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS theories.The paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded conditions.The paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.
基金Supported by the Natural Science Foundation of Hubei Province(2021CFB275)National Natural Science Foundation of China(12301667).
文摘In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Using the coupling method,we obtain the existence of a full absorbing set on which continuous time Markov processes are f-geometric ergodic.
基金Supported by Jiangsu Key R&D Program(BE2021622)Jiangsu Postgraduate Practice and Innovation Program(SJCX23_0395).
文摘Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.
基金Supported by the Major Science and Technology Projects in Jilin Province and Changchun City(20220301010GX).
文摘When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.
基金supported by the National Natural Science Foundation of China(Nos.92461313,12074387,and 92161114)the Innovation Capability Support Program of Shaanxi Province(No.2023-CX-TD-49).
文摘The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment energy of Co_(2)Ge_(10)^(-)was measured to be 2.86±0.08 eV.The lowest-energy isomer of Co_(2)Ge_(10)^(-)is in a doublet state and has a cage-like structure with Cs symmetry,which can be constructed by a tetragonal bipyramid on top of a pentagonal bipyramid and these two bipyramid structures share a common Co atom.The most stable structure of neutral Co_(2)Ge_(10)resembles its anionic counterpart and it is in a triplet state.The natural population analysis showed that the inner Co atom of both the anionic and neutral Co_(2)Ge_(10)acquires negative charge from the neighboring Ge atoms.The outer Co atom has a larger spin moment than the inner Co atom,indicating that the magnetic moments of Co_(2)Ge_(10)^(-/0)are mainly contributed by the outer Co atom.Analyses of the density of states and molecular orbitals indicated that there are a few highly delocalized molecular orbitals in Co_(2)Ge_(10)^(-),which are mainly contributed by Ge 4s atomic orbitals.
基金Supported by the Higher Education Science Research Project(Natural Science)of Anhui Province(Grant No.2023AH050487)。
文摘In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values in certain specific Banach spaces.Next,we investigate the relationships between this new constant and other classical constants.Specifically,we establish an inequality relationship between it and the J(X)constant,as well as an identity relationship between it and theρX(t)constant.Furthermore,we characterize some geometric properties of Banach spaces by means of this new constant.Finally,by restricting the above-mentioned constant to the unit sphere,we introduce another new constant,calculate its upper and lower bounds,and present a relevant example.
基金supported by National Major Scientific Research Instrument Development Project of China(No.51927804)Science Fund for Shaanxi Provincial Department of Education's Youth Innovation Team Research Plan under Grant(No.23JP169).
文摘In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.
文摘This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accuracy of the solution are studied using two columns,two braced frames,and one unbraced frame.Discussion is provided when the new geometric stiffness matrix can be used to improve the buckling load analysis results and when it may provide only nominal additional benefit.
基金Supported by Shanxi Provincial Natural Science Foundation(Grant No.2021JM010)The Youth Innovation Team of Shaanxi Universities.
文摘This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.
基金supported by the Key Technology of Flexible Regulation of Energy in Green High-Efficiency/Carbon-Efficient Buildings under the Smart Park System of PowerChina Guiyang Co.,Ltd.(YJ2022-12)the Science and Technology Support Plan of Guizhou Province“Research and Application Development of Key Technologies for Flexible Regulation of Energy in High-Efficiency/Carbon-Efficient Buildings”(Guizhou Science and Technology Cooperation Support[2023]General 409).
文摘In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.
基金supported by the National Natural Science Foundation of China(Grant Nos.11564013 and 11964010)the Natural Science Foundation of Hunan Province(Grant No.2020JJ4495)the Scientific Research Fund of Hunan Provincial Education Department,China(Grant Nos.22A0377 and 21A0333).
文摘Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under both weak and strong qubit-reservoir coupling regimes.The multiqubit system is connected with either a common bosonic reservoir(CBR)or multiple independent bosonic reservoirs(IBRs).In the CBR case,our findings indicate that both QD and GQD can be strengthened by increasing the number of qubits in the multiqubit system.Furthermore,we study the steady state QD and GQD in the strong coupling regime,and find that the stable value in the long-time limit is determined exclusively by the number of qubits.The evolution period of QD and GQD gets longer as the dipole–dipole interaction(DDI)strength increases,which helps prolong the correlation time and thus preserves the quantum correlation under the weak coupling regime.Further analysis reveals notable differences between the CBR and IBRs scenarios.In the IBRs case,the decay of QD and GQD becomes slower compared to the CBR case,with both measures tending to zero at a reduced rate.Moreover,GQD consistently exhibits lower values than QD in both scenarios.These findings provide valuable insights into the selection of appropriate correlation measurement techniques for quantifying quantum correlations.
基金the National Natural Science Foundation of China(No.61962032)。
文摘In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.
文摘This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.
基金supported by the National Natural Science Foundation of China(Grant Nos.12304560,92265113,12074368,and 12034018)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302300)China Postdoctoral Science Foundation(Grant Nos.BX20220281 and 2023M733408).
文摘Geometric phase gates have attracted considerable attention due to their intrinsic robustness against certain types of noise.Significant progress has been achieved in implementing geometric phase gates using microwave control in siliconbased electron spin systems.In this work,we propose an alternative geometric phase gate protocol that differs fundamentally from microwave driving approaches by leveraging square-wave control of rapidly switchable micromagnets driven by spin-orbit torque(SOT)to achieve fast and precise magnetic field modulation.By employing square-wave currents to control magnetization switching,our approach relaxes the requirements on waveform precision while significantly suppressing crosstalk.Moreover,our scheme inherently preserves trajectory closure at the end of each operation,effectively mitigating noise-induced path deviation and enhancing gate robustness even under strong noise conditions,thereby offering a promising pathway toward efficient and reliable quantum operations in large-scale qubit arrays.
