Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in...Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in accuracy and efficiency.To address these challenges,we propose an adaptive multi-learning cooperation search algorithm(AMLCSA)for efficient identification of unknown parameters in PV models.AMLCSA is a novel algorithm inspired by teamwork behaviors in modern enterprises.It enhances the original cooperation search algorithm in two key aspects:(i)an adaptive multi-learning strategy that dynamically adjusts search ranges using adaptive weights,allowing better individuals to focus on local exploitation while guiding poorer individuals toward global exploration;and(ii)a chaotic grouping reflection strategy that introduces chaotic sequences to enhance population diversity and improve search performance.The effectiveness of AMLCSA is demonstrated on single-diode,double-diode,and three PV-module models.Simulation results show that AMLCSA offers significant advantages in convergence,accuracy,and stability compared to existing state-of-the-art algorithms.展开更多
The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents consid...The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.展开更多
A dual-arm nursing robot can gently lift patients and transfer them between a bed and a wheelchair.With its lightweight design,high load-bearing capacity,and smooth surface,the coupled-drive joint is particularly well...A dual-arm nursing robot can gently lift patients and transfer them between a bed and a wheelchair.With its lightweight design,high load-bearing capacity,and smooth surface,the coupled-drive joint is particularly well suited for these robots.However,the coupled nature of the joint disrupts the direct linear relationship between the input and output torques,posing challenges for dynamic modeling and practical applications.This study investigated the transmission mechanism of this joint and employed the Lagrangian method to construct a dynamic model of its internal dynamics.Building on this foundation,the Newton-Euler method was used to develop a dynamic model for the entire robotic arm.A continuously differentiable friction model was incorporated to reduce the vibrations caused by speed transitions to zero.An experimental method was designed to compensate for gravity,inertia,and modeling errors to identify the parameters of the friction model.This method establishes a mapping relationship between the friction force and motor current.In addition,a Fourier series-based excitation trajectory was developed to facilitate the identification of the dynamic model parameters of the robotic arm.Trajectory tracking experiments were conducted during the experimental validation phase,demonstrating the high accuracy of the dynamic model and the parameter identification method for the robotic arm.This study presents a dynamic modeling and parameter identification method for coupled-drive joint robotic arms,thereby establishing a foundation for motion control in humanoid nursing robots.展开更多
Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,...Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.展开更多
Soft materials,with the sensitivity to various external stimuli,exhibit high flexibility and stretchability.Accurate prediction of their mechanical behaviors requires advanced hyperelastic constitutive models incorpor...Soft materials,with the sensitivity to various external stimuli,exhibit high flexibility and stretchability.Accurate prediction of their mechanical behaviors requires advanced hyperelastic constitutive models incorporating multiple parameters.However,identifying multiple parameters under complex deformations remains a challenge,especially with limited observed data.In this study,we develop a physics-informed neural network(PINN)framework to identify material parameters and predict mechanical fields,focusing on compressible Neo-Hookean materials and hydrogels.To improve accuracy,we utilize scaling techniques to normalize network outputs and material parameters.This framework effectively solves forward and inverse problems,extrapolating continuous mechanical fields from sparse boundary data and identifying unknown mechanical properties.We explore different approaches for imposing boundary conditions(BCs)to assess their impacts on accuracy.To enhance efficiency and generalization,we propose a transfer learning enhanced PINN(TL-PINN),allowing pre-trained networks to quickly adapt to new scenarios.The TL-PINN significantly reduces computational costs while maintaining accuracy.This work holds promise in addressing practical challenges in soft material science,and provides insights into soft material mechanics with state-of-the-art experimental methods.展开更多
In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parame...In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.展开更多
In light of the high nonlinearity of LuGre friction model, a novel method based on ant colony algorithm(ACA) for identifying the friction parameters of flight simulation servo system is proposed. ACA is a parallelized...In light of the high nonlinearity of LuGre friction model, a novel method based on ant colony algorithm(ACA) for identifying the friction parameters of flight simulation servo system is proposed. ACA is a parallelized bionic optimization algorithm inspired from the behavior of real ants, and a kind of positive feedback mechanism is adopted in ACA. On the basis of brief introduction of LuGre friction model, a method for identifying the static LuGre friction parameters and the dynamic LuGre friction parameters using ACA is derived. Finally, this new friction parameter identification scheme is applied to a electric-driven flight simulation servo system with high precision. Simulation and application results verify the feasibility and the effectiveness of the scheme. It provides a new way to identify the friction parameters of LuGre model.展开更多
To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is dev...To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.展开更多
Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a ...Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.展开更多
In order to evaluate the nonlinear performance and the possible damage to rubber-bearings （RBs） during their normal operation or under strong earthquakes, a simplified Bouc-Wen model is used to describe the nonlinea...In order to evaluate the nonlinear performance and the possible damage to rubber-bearings （RBs） during their normal operation or under strong earthquakes, a simplified Bouc-Wen model is used to describe the nonlinear hysteretic behavior of RBs in this paper, which has the advantages of being smooth-varying and physically motivated. Further, based on the results from experimental tests performed by using a particular type of RB （GZN 110） under different excitation scenarios, including white noise and several earthquakes, a new system identification method, referred to as the sequential nonlinear least- square estimation （SNLSE）, is introduced to identify the model parameters. It is shown that the proposed simplified Bouc- Wen model is capable of describing the nonlinear hysteretic behavior of RBs, and that the SNLSE approach is very effective in identifying the model parameters of RBs.展开更多
Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity ana...Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.展开更多
Recently, frequency-based least-squares （LS） estimators have found wide application in identifying aircraft flutter parameters. However, the frequency methods are often known to suffer from numerical difficulties wh...Recently, frequency-based least-squares （LS） estimators have found wide application in identifying aircraft flutter parameters. However, the frequency methods are often known to suffer from numerical difficulties when identifying a continuous-time model, especially, of broader frequency or higher order. In this article, a numerically robust LS estimator based on vector orthogonal polynomial is proposed to solve the numerical problem of multivariable systems and applied to the flutter testing. The key idea of this method is to represent the frequency response function （FRF） matrix by a right matrix fraction description （RMFD） model, and expand the numerator and denominator polynomial matrices on a vector orthogonal basis. As a result, a perfect numerical condition （numerical condition equals 1） can be obtained for linear LS estimator. Finally, this method is verified by flutter test of a wing model in a wind tunnel and real flight flutter test of an aircraft. The results are compared to those with notably LMS PolyMAX, which is not troubled by the numerical problem as it is established in z domain （e.g. derived from a discrete-time model）. The verification has evidenced that this method, apart from overcoming the numerical problem, yields the results comparable to those acquired with LMS PolyMAX, or even considerably better at some frequency bands.展开更多
Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential ro...Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high arch dams is proposed. The proposed procedure is implemented by combining the densitybased spatial clustering of applications with noise(DBSCAN) algorithm and the stochastic subspace identification(SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierarchical clustering algorithms. In addition, the errors of the identified frequencies of the arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of arch dams.展开更多
A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear cont...A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.展开更多
An estimation approach using least squares method was presented for identificationof model parameters of pressure control in shield tunneling.The state equation ofthe pressure control system for shield tunneling was a...An estimation approach using least squares method was presented for identificationof model parameters of pressure control in shield tunneling.The state equation ofthe pressure control system for shield tunneling was analytically derived based on themass equilibrium principle that the entry mass of the pressure chamber from cutting headwas equal to excluding mass from the screw conveyor.The randomly observed noise wasnumerically simulated and mixed to simulated observation values of system responses.The numerical simulation shows that the state equation of the pressure control system forshield tunneling is reasonable and the proposed estimation approach is effective even ifthe random observation noise exists.The robustness of the controlling procedure is validatedby numerical simulation results.展开更多
In order to better identify the parameters of the fractional-order system,a modified particle swarm optimization(MPSO)algorithm based on an improved Tent mapping is proposed.The MPSO algorithm is validated with eight ...In order to better identify the parameters of the fractional-order system,a modified particle swarm optimization(MPSO)algorithm based on an improved Tent mapping is proposed.The MPSO algorithm is validated with eight classical test functions,and compared with the POS algorithm with adaptive time varying accelerators(ACPSO),the genetic algorithm(GA),a d the improved PSO algorithm with passive congregation(IPSO).Based on the systems with known model structures a d unknown model structures,the proposed algorithm is adopted to identify two typical fractional-order models.The results of parameter identification show that the application of average value of position information is beneficial to making f 11 use of the information exchange among individuals and speeds up the global searching speed.By introducing the uniformity and ergodicity of Tent mapping,the MPSO avoids the extreme v^ue of position information,so as not to fall into the local optimal value.In brief the MPSOalgorithm is an effective a d useful method with a fast convergence rate and high accuracy.展开更多
Accuracy of the motor parameters is important in realizing high performance control of permanent magnet synchronous motor(PMSM).However,the inductance and resistance of motor winding vary with the change of temperatur...Accuracy of the motor parameters is important in realizing high performance control of permanent magnet synchronous motor(PMSM).However,the inductance and resistance of motor winding vary with the change of temperature,rotor position and current frequency.In this paper,a technology based on circuit model is introduced for realizing online identification of the parameter of PMSM.In the proposed method,a set of nonlinear equations containing the parameters to be identified is established.Considering that it is very difficult to obtain the analytical solution of a nonlinear system of equations,Newton iterative method is used for solving the equations.Both the simulation and testing results confirm the effectiveness of the method presented.展开更多
Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the...Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.展开更多
Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the princ...Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the principle of aircraft icing and its effects on flight performance. The onboard icing detection equipment can only give the qualitative icing information, but cannot effectively describe how serious the consequences would be. If the icing detection equipment fails, it will cause a serious threat to flight safety. This paper reviews the smart icing system and its fundamental principle. Then based on H∞ theory, an aircraft icing parameter identification method is introduced, and its feasibility is verified by simulation results. Moreover, this method can work normally under noise interference and measurement error. Icing parameter identification method can also test part of aircraft's stability or control derivatives which would be changed obviously after aircraft icing. Classified by neural networks, the stability or control derivatives' variation can be mapped to ice parameters' variation that reflects the severity of aircraft icing. Then H2 state feedback control is designed originally to suppress the impact of noise interference, so aircraft can keep steady after it is iced. Seeing from simulation result of the whole system, it is clear that the system can effectively detect icing parameters and by using feedback control system, it can ensure the safety of aircraft in the flight envelope.展开更多
A new experimental apparatus was set up to investigate the actual fi-iction characteristics on the basis of speed control of the serve system.A modified friction model was proposed due to real time varying deformation...A new experimental apparatus was set up to investigate the actual fi-iction characteristics on the basis of speed control of the serve system.A modified friction model was proposed due to real time varying deformation resistance.The approach to identify the parameters of comprehensive friction behaviors based on the modified model was proposed and applied to the forging press.The impacts on parameters which the external load had were also investigated.The results show that friction force decreases with velocity in the low velocity regime whereas the friction force increases with the velocity in the high velocity regime under no external load.It is also shown that the Coulomb friction force,the maximum static friction force and the vicious friction coefficient change linearly with the external load taking the velocity at which the magnitude of the steady state friction force becomes minimum as the critical velocity.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62303197,62273214)the Natural Science Foundation of Shandong Province(ZR2024MFO18).
文摘Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in accuracy and efficiency.To address these challenges,we propose an adaptive multi-learning cooperation search algorithm(AMLCSA)for efficient identification of unknown parameters in PV models.AMLCSA is a novel algorithm inspired by teamwork behaviors in modern enterprises.It enhances the original cooperation search algorithm in two key aspects:(i)an adaptive multi-learning strategy that dynamically adjusts search ranges using adaptive weights,allowing better individuals to focus on local exploitation while guiding poorer individuals toward global exploration;and(ii)a chaotic grouping reflection strategy that introduces chaotic sequences to enhance population diversity and improve search performance.The effectiveness of AMLCSA is demonstrated on single-diode,double-diode,and three PV-module models.Simulation results show that AMLCSA offers significant advantages in convergence,accuracy,and stability compared to existing state-of-the-art algorithms.
基金supported by the National Key Research and Development Program of China(No.2023YFC3010400)。
文摘The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.
基金Supported by Shanghai Municipal Science and Technology Program (Grant No.21511101701)National Key Research and Development Program of China (Grant No.2021YFC0122704)。
文摘A dual-arm nursing robot can gently lift patients and transfer them between a bed and a wheelchair.With its lightweight design,high load-bearing capacity,and smooth surface,the coupled-drive joint is particularly well suited for these robots.However,the coupled nature of the joint disrupts the direct linear relationship between the input and output torques,posing challenges for dynamic modeling and practical applications.This study investigated the transmission mechanism of this joint and employed the Lagrangian method to construct a dynamic model of its internal dynamics.Building on this foundation,the Newton-Euler method was used to develop a dynamic model for the entire robotic arm.A continuously differentiable friction model was incorporated to reduce the vibrations caused by speed transitions to zero.An experimental method was designed to compensate for gravity,inertia,and modeling errors to identify the parameters of the friction model.This method establishes a mapping relationship between the friction force and motor current.In addition,a Fourier series-based excitation trajectory was developed to facilitate the identification of the dynamic model parameters of the robotic arm.Trajectory tracking experiments were conducted during the experimental validation phase,demonstrating the high accuracy of the dynamic model and the parameter identification method for the robotic arm.This study presents a dynamic modeling and parameter identification method for coupled-drive joint robotic arms,thereby establishing a foundation for motion control in humanoid nursing robots.
基金supported by the Natural Science Foundation of Shanghai(No.23ZR1429300)Innovation Funds of CNNC(Lingchuang Fund,Contract No.CNNC-LCKY-202234)the Project of the Nuclear Power Technology Innovation Center of Science Technology and Industry(No.HDLCXZX-2023-HD-039-02)。
文摘Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.
基金supported by the National Natural Science Foundation of China(Nos.12172273 and 11820101001)。
文摘Soft materials,with the sensitivity to various external stimuli,exhibit high flexibility and stretchability.Accurate prediction of their mechanical behaviors requires advanced hyperelastic constitutive models incorporating multiple parameters.However,identifying multiple parameters under complex deformations remains a challenge,especially with limited observed data.In this study,we develop a physics-informed neural network(PINN)framework to identify material parameters and predict mechanical fields,focusing on compressible Neo-Hookean materials and hydrogels.To improve accuracy,we utilize scaling techniques to normalize network outputs and material parameters.This framework effectively solves forward and inverse problems,extrapolating continuous mechanical fields from sparse boundary data and identifying unknown mechanical properties.We explore different approaches for imposing boundary conditions(BCs)to assess their impacts on accuracy.To enhance efficiency and generalization,we propose a transfer learning enhanced PINN(TL-PINN),allowing pre-trained networks to quickly adapt to new scenarios.The TL-PINN significantly reduces computational costs while maintaining accuracy.This work holds promise in addressing practical challenges in soft material science,and provides insights into soft material mechanics with state-of-the-art experimental methods.
基金the Natural Science Foundation of China under Grant 52077027in part by the Liaoning Province Science and Technology Major Project No.2020JH1/10100020.
文摘In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.
文摘In light of the high nonlinearity of LuGre friction model, a novel method based on ant colony algorithm(ACA) for identifying the friction parameters of flight simulation servo system is proposed. ACA is a parallelized bionic optimization algorithm inspired from the behavior of real ants, and a kind of positive feedback mechanism is adopted in ACA. On the basis of brief introduction of LuGre friction model, a method for identifying the static LuGre friction parameters and the dynamic LuGre friction parameters using ACA is derived. Finally, this new friction parameter identification scheme is applied to a electric-driven flight simulation servo system with high precision. Simulation and application results verify the feasibility and the effectiveness of the scheme. It provides a new way to identify the friction parameters of LuGre model.
基金Supported by the National Natural Science Foundation of China(10902051)the Natural Science Foundation of Jiangsu Province(BK2008046)~~
文摘To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.
基金supported by the National Defense Basic Research Program of China(No.B22201320xx)
文摘Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.
基金National Natural Science Foundation of China Under Grant No.10572058the Science Foundation of Aeronautics of China Under Grant No.2008ZA52012
文摘In order to evaluate the nonlinear performance and the possible damage to rubber-bearings （RBs） during their normal operation or under strong earthquakes, a simplified Bouc-Wen model is used to describe the nonlinear hysteretic behavior of RBs in this paper, which has the advantages of being smooth-varying and physically motivated. Further, based on the results from experimental tests performed by using a particular type of RB （GZN 110） under different excitation scenarios, including white noise and several earthquakes, a new system identification method, referred to as the sequential nonlinear least- square estimation （SNLSE）, is introduced to identify the model parameters. It is shown that the proposed simplified Bouc- Wen model is capable of describing the nonlinear hysteretic behavior of RBs, and that the SNLSE approach is very effective in identifying the model parameters of RBs.
基金supported by the National Natural Science Foundation of China (Grant No. 41271003)the National Basic Research Program of China (Grants No. 2010CB428403 and 2010CB951103)
文摘Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
基金Foundation items： Aeronautical Science Foundation of China （2007ZD53053） NPU Foundation for Fundamental Research （NPU-FFR-W018104）
文摘Recently, frequency-based least-squares （LS） estimators have found wide application in identifying aircraft flutter parameters. However, the frequency methods are often known to suffer from numerical difficulties when identifying a continuous-time model, especially, of broader frequency or higher order. In this article, a numerically robust LS estimator based on vector orthogonal polynomial is proposed to solve the numerical problem of multivariable systems and applied to the flutter testing. The key idea of this method is to represent the frequency response function （FRF） matrix by a right matrix fraction description （RMFD） model, and expand the numerator and denominator polynomial matrices on a vector orthogonal basis. As a result, a perfect numerical condition （numerical condition equals 1） can be obtained for linear LS estimator. Finally, this method is verified by flutter test of a wing model in a wind tunnel and real flight flutter test of an aircraft. The results are compared to those with notably LMS PolyMAX, which is not troubled by the numerical problem as it is established in z domain （e.g. derived from a discrete-time model）. The verification has evidenced that this method, apart from overcoming the numerical problem, yields the results comparable to those acquired with LMS PolyMAX, or even considerably better at some frequency bands.
基金National Natural Science Foundation of China under Grant Nos. 51725901 and 51639006。
文摘Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high arch dams is proposed. The proposed procedure is implemented by combining the densitybased spatial clustering of applications with noise(DBSCAN) algorithm and the stochastic subspace identification(SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierarchical clustering algorithms. In addition, the errors of the identified frequencies of the arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of arch dams.
基金Project(2015BAG06B00)supported by the National Key Technology Research from Development Program of the Ministry of Science and Technology of China
文摘A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.
基金Supported by the National Basic Research Program of China(2007CB714006)the National Natural Science Foundation of China(90815023)
文摘An estimation approach using least squares method was presented for identificationof model parameters of pressure control in shield tunneling.The state equation ofthe pressure control system for shield tunneling was analytically derived based on themass equilibrium principle that the entry mass of the pressure chamber from cutting headwas equal to excluding mass from the screw conveyor.The randomly observed noise wasnumerically simulated and mixed to simulated observation values of system responses.The numerical simulation shows that the state equation of the pressure control system forshield tunneling is reasonable and the proposed estimation approach is effective even ifthe random observation noise exists.The robustness of the controlling procedure is validatedby numerical simulation results.
基金The National Natural Science Foundation of China(No.61374153,61473138,61374133)the Natural Science Foundation of Jiangsu Province(No.BK20151130)+1 种基金Six Talent Peaks Project in Jiangsu Province(No.2015-DZXX-011)China Scholarship Council Fund(No.201606845005)
文摘In order to better identify the parameters of the fractional-order system,a modified particle swarm optimization(MPSO)algorithm based on an improved Tent mapping is proposed.The MPSO algorithm is validated with eight classical test functions,and compared with the POS algorithm with adaptive time varying accelerators(ACPSO),the genetic algorithm(GA),a d the improved PSO algorithm with passive congregation(IPSO).Based on the systems with known model structures a d unknown model structures,the proposed algorithm is adopted to identify two typical fractional-order models.The results of parameter identification show that the application of average value of position information is beneficial to making f 11 use of the information exchange among individuals and speeds up the global searching speed.By introducing the uniformity and ergodicity of Tent mapping,the MPSO avoids the extreme v^ue of position information,so as not to fall into the local optimal value.In brief the MPSOalgorithm is an effective a d useful method with a fast convergence rate and high accuracy.
文摘Accuracy of the motor parameters is important in realizing high performance control of permanent magnet synchronous motor(PMSM).However,the inductance and resistance of motor winding vary with the change of temperature,rotor position and current frequency.In this paper,a technology based on circuit model is introduced for realizing online identification of the parameter of PMSM.In the proposed method,a set of nonlinear equations containing the parameters to be identified is established.Considering that it is very difficult to obtain the analytical solution of a nonlinear system of equations,Newton iterative method is used for solving the equations.Both the simulation and testing results confirm the effectiveness of the method presented.
基金Project(xjj20100078) supported by the Fundamental Research Funds for the Central Universities in China
文摘Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.
基金the China Postdoctoral Science Foundation （No. 20100480588）
文摘Aircraft icing accident happens frequently. Researchers try to find new ways to solve this problem. The study is facing the direction of intelligent inspection and control system. Previous studies focused on the principle of aircraft icing and its effects on flight performance. The onboard icing detection equipment can only give the qualitative icing information, but cannot effectively describe how serious the consequences would be. If the icing detection equipment fails, it will cause a serious threat to flight safety. This paper reviews the smart icing system and its fundamental principle. Then based on H∞ theory, an aircraft icing parameter identification method is introduced, and its feasibility is verified by simulation results. Moreover, this method can work normally under noise interference and measurement error. Icing parameter identification method can also test part of aircraft's stability or control derivatives which would be changed obviously after aircraft icing. Classified by neural networks, the stability or control derivatives' variation can be mapped to ice parameters' variation that reflects the severity of aircraft icing. Then H2 state feedback control is designed originally to suppress the impact of noise interference, so aircraft can keep steady after it is iced. Seeing from simulation result of the whole system, it is clear that the system can effectively detect icing parameters and by using feedback control system, it can ensure the safety of aircraft in the flight envelope.
基金Project(51005251)supported by the National Natural Science Foundation of ChinaProject(2011CB706802)supported by the National Basic Research Development Program of China(973 Program)
文摘A new experimental apparatus was set up to investigate the actual fi-iction characteristics on the basis of speed control of the serve system.A modified friction model was proposed due to real time varying deformation resistance.The approach to identify the parameters of comprehensive friction behaviors based on the modified model was proposed and applied to the forging press.The impacts on parameters which the external load had were also investigated.The results show that friction force decreases with velocity in the low velocity regime whereas the friction force increases with the velocity in the high velocity regime under no external load.It is also shown that the Coulomb friction force,the maximum static friction force and the vicious friction coefficient change linearly with the external load taking the velocity at which the magnitude of the steady state friction force becomes minimum as the critical velocity.
