It is a difficult problem to study the stability of the rheonomic and nonholonomic mechanical systems. Especially it is difficult to construct the Lyapunov function directly from the differential equation. But the gra...It is a difficult problem to study the stability of the rheonomic and nonholonomic mechanical systems. Especially it is difficult to construct the Lyapunov function directly from the differential equation. But the gradient system is exactly suitable to study the stability of a dynamical system with the aid of the Lyapunov function. The stability of the solution for a simple rheonomic nonholonomic constrained system is studied in this paper. Firstly, the differential equations of motion of the system are established. Secondly, a problem in which the generalized forces are exerted on the system such that the solution is stable is proposed. Finally, the stable solutions of the rheonomic nonholonomic system can be constructed by using the gradient systems.展开更多
In this paper the generalized Bianchi's identities for the variant constrained system (GBIVOS)w ith non-invariant action integral and constraint conditions was derived, and the strong and weak conservation laws fo...In this paper the generalized Bianchi's identities for the variant constrained system (GBIVOS)w ith non-invariant action integral and constraint conditions was derived, and the strong and weak conservation laws for such system was deduced. The preliminary applications of the GBIVCS to the case for some models of field theories was given. The Dirac constraint of such system was discussed.展开更多
We discuss the stationarity of generator G for gauge symmetries in two directions.One is to the motion equations defined by total Hamiltonian H T,and gives that the number of the independent coefficients in the genera...We discuss the stationarity of generator G for gauge symmetries in two directions.One is to the motion equations defined by total Hamiltonian H T,and gives that the number of the independent coefficients in the generator G is not greater than the number of the primary first-class constraints,and the number of Noether conserved charges is not greater than that of the primary first-class constraints,too.The other is to the variances of canonical variables deduced from the generator G,and gives the variances of Lagrangian multipliers contained in extended Hamiltonian H E.And a second-class constraint generated by a first-class constraint may imply a new first-class constraint which can be combined by introducing other second-class constraints.Finally,we supply two examples.One with three first-class constraints(two is primary and one is secondary) has two Noether conserved charges,and the secondary first-class constraint is combined by three second-class constraints which are a secondary and two primary second-class constraints.The other with two first-class constraints(one is primary and one is secondary) has one Noehter conserved charge.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
Switched systems play an imperative role in modeling many real industrial systems with abrupt changes.Due to possible exposure to unreliable and complex physical environments,switching dynamics may simultaneously face...Switched systems play an imperative role in modeling many real industrial systems with abrupt changes.Due to possible exposure to unreliable and complex physical environments,switching dynamics may simultaneously face multiple faults,including the unexpected controller disconnect,the temporary mismatch between subsystems and desired corresponding controllers,and the intermittent disordering of mode transitions.These commonly arising faults may result in severe and detrimental impacts on the reliability and convergence of the closed-loop solution,thereby bringing significant yet challenging issues to be tackled.This paper provides the first attempt to investigate the stabilization problem for a class of constrained switched linear systems with multiple faults under mode-dependent dwell time(MDT).From a set-theory perspective,we demonstrate a critical necessary and sufficient stability condition for switched systems without uncertainties.Moreover,the non-conservative stability criterion is further extended to the perturbed switched systems with rigorous proof.A switching communication network example verifies the validity of the theoretical result and demonstrates their advantages.展开更多
The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in futu...The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.展开更多
This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller fo...This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.展开更多
Singular systems within combined fractional derivatives are established.Firstly,the fractional Lagrange equation is analyzed.Secondly,the fractional primary constraint is given.Thirdly,the Noether and Lie symmetry met...Singular systems within combined fractional derivatives are established.Firstly,the fractional Lagrange equation is analyzed.Secondly,the fractional primary constraint is given.Thirdly,the Noether and Lie symmetry methods of fractional constrained Hamiltonian system are studied.Finally,the obtained results are illustrated with an example.展开更多
This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynami...This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.展开更多
This article presents an event-triggered H_(∞) consensus control scheme using reinforcement learning (RL) for nonlinear second-order multi-agent systems (MASs) with control constraints. First, considering control con...This article presents an event-triggered H_(∞) consensus control scheme using reinforcement learning (RL) for nonlinear second-order multi-agent systems (MASs) with control constraints. First, considering control constraints, the constrained H_(∞) consensus problem is transformed into a multi-player zero-sum game with non-quadratic performance functions. Then, an event-triggered control method is presented to conserve communication resources and a new triggering condition is developed for each agent to make the triggering threshold independent of the disturbance attenuation level. To derive the optimal controller that can minimize the cost function in the case of worst disturbance, a constrained Hamilton–Jacobi–Bellman (HJB) equation is defined. Since it is difficult to solve analytically due to its strongly non-linearity, reinforcement learning (RL) is implemented to obtain the optimal controller. In specific, the optimal performance function and the worst-case disturbance are approximated by a time-triggered critic network;meanwhile, the optimal controller is approximated by event-triggered actor network. After that, Lyapunov analysis is utilized to prove the uniformly ultimately bounded (UUB) stability of the system and that the network weight errors are UUB. Finally, a simulation example is utilized to demonstrate the effectiveness of the control strategy provided.展开更多
The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical ...The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical output still remains a significant challenge.Here,a strategy of inducing constrained phase separation on single nanofibers via shear force was proposed.Employing electrospinning technology,a polyacrylonitrile/polyvinylidene difluoride(PAN/PVDF)nanofibrous membrane was fabricated in one step,which enabled simultaneous piezoelectric and triboelectric conversion within a single-layer membrane.Each nanofiber contained independent components of PAN and PVDF and exhibited a rough surface.The abundant frictional contact points formed between these heterogeneous components contributed to an enhanced endogenous triboelectric output,showcasing an excellent synergistic effect of piezoelectric and triboelectric response in the nanofibrous membrane.Additionally,the component mass ratio influenced the microstructure,piezoelectric conformation and piezoelectric performance of the PAN/PVDF nanofibrous membranes.Through comprehensive performance comparison,the optimal mass ratio of PAN to PVDF was determined to be 9∶1.The piezoelectric devices made of the optimal PAN/PVDF nanofibrous membranes with rough nanofiber surfaces generated an output voltage of 20 V,which was about 1.8 times that of the smooth one at the same component mass ratio.The strategy of constrained phase separation on the surface of individual nanofibers provides a new approach to enhance the output performance of single-layer piezoelectric nanofibrous materials.展开更多
Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a ...Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.展开更多
Geochemical survey data are essential across Earth Science disciplines but are often affected by noise,which can obscure important geological signals and compromise subsequent prediction and interpretation.Quantifying...Geochemical survey data are essential across Earth Science disciplines but are often affected by noise,which can obscure important geological signals and compromise subsequent prediction and interpretation.Quantifying prediction uncertainty is hence crucial for robust geoscientific decision-making.This study proposes a novel deep learning framework,the Spatially Constrained Variational Autoencoder(SC-VAE),for denoising geochemical survey data with integrated uncertainty quantification.The SC-VAE incorporates spatial regularization,which enforces spatial coherence by modeling inter-sample relationships directly within the latent space.The performance of the SC-VAE was systematically evaluated against a standard Variational Autoencoder(VAE)using geochemical data from the gold polymetallic district in the northwestern part of Sichuan Province,China.Both models were optimized using Bayesian optimization,with objective functions specifically designed to maintain essential geostatistical characteristics.Evaluation metrics include variogram analysis,quantitative measures of spatial interpolation accuracy,visual assessment of denoised maps,and statistical analysis of data distributions,as well as decomposition of uncertainties.Results show that the SC-VAE achieves superior noise suppression and better preservation of spatial structure compared to the standard VAE,as demonstrated by a significant reduction in the variogram nugget effect and an increased partial sill.The SC-VAE produces denoised maps with clearer anomaly delineation and more regularized data distributions,effectively mitigating outliers and reducing kurtosis.Additionally,it delivers improved interpolation accuracy and spatially explicit uncertainty estimates,facilitating more reliable and interpretable assessments of prediction confidence.The SC-VAE framework thus provides a robust,geostatistically informed solution for enhancing the quality and interpretability of geochemical data,with broad applicability in mineral exploration,environmental geochemistry,and other Earth Science domains.展开更多
Altermagnetism,a recently identified class of collinear magnetism,combines key features of antiferromagnets and ferromagnets.Despite having zero net magnetization,altermagnetic materials exhibit anomalous transport ef...Altermagnetism,a recently identified class of collinear magnetism,combines key features of antiferromagnets and ferromagnets.Despite having zero net magnetization,altermagnetic materials exhibit anomalous transport effects,including the anomalous Hall,Nernst,and thermal Hall effects,as well as magneto-optical Kerr and Faraday effects.These phenomena,previously thought unique to ferromagnets,are dictated by symmetry,as confirmed by density functional theory(DFT)calculations.However,an effective model-based approach to verify these symmetry constraints remains unavailable.In this Letter,we construct a k·ρ model for d-wave altermagnets CuX_(2)(X=F,Cl)using spin space group representations and apply it to calculate the anomalous Hall effect.The symmetry-imposed transport properties predicted by the model are in agreement with the DFT results,providing a foundation for further investigation into symmetry-restricted transport phenomena in altermagnetic materials.展开更多
Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they re...Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.展开更多
This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into accoun...This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into account recent progress and addressing these concerns separately, there remains a lack of solutions offering theoretical guarantees for both privacy protection and constrained ZOO over time-varying unbalanced graphs.We hereby propose a novel algorithm, termed the differential privacy(DP) distributed push-sum based zeroth-order constrained optimization algorithm(DP-ZOCOA). Operating over time-varying unbalanced graphs, DP-ZOCOA obviates the need for supplemental suboptimization problem computations, thereby reducing overhead in comparison to distributed primary-dual methods. DP-ZOCOA is specifically tailored to tackle constrained ZOO problems over time-varying unbalanced graphs,offering a guarantee of convergence to the optimal solution while robustly preserving privacy. Moreover, we provide rigorous proofs of convergence and privacy for DP-ZOCOA, underscoring its efficacy in attaining optimal convergence without constraints. To enhance its applicability, we incorporate DP-ZOCOA into the federated learning framework and formulate a decentralized zeroth-order constrained federated learning algorithm(ZOCOA-FL) to address challenges stemming from the timevarying imbalance of communication topology. Finally, the performance and effectiveness of the proposed algorithms are thoroughly evaluated through simulations on distributed least squares(DLS) and decentralized federated learning(DFL) tasks.展开更多
Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across vari...Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.展开更多
This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired traje...This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.展开更多
To reduce the number of the level sets used in algorithm of constrained nonlinear systems via ellipsoidal techniques, according to the analysis of mathematics, searching algorithm is used for choosing the control inpu...To reduce the number of the level sets used in algorithm of constrained nonlinear systems via ellipsoidal techniques, according to the analysis of mathematics, searching algorithm is used for choosing the control input. Simulation shows that the number of level sets used for controlling is almost the same as that used in polytope techniques. Sub time optimal algorithm reduces the number of the level sets used in ellipsoidal techniques.展开更多
For an in-depth study on the integration problem of the constrained mechanical systems the method of integration for the Birkhoffian system with constraints is discussed and the method of variation of parameters for s...For an in-depth study on the integration problem of the constrained mechanical systems the method of integration for the Birkhoffian system with constraints is discussed and the method of variation of parameters for solving the dynamical equations of the constrained Birkhoffian system is provided.First the differential equations of motion for the constrained Birkhoffian system as well as for the corresponding free Birkhoffian system are established.Secondly a system of auxiliary equations is constructed and the general solution of the equations is found.Finally by varying the parameters and utilizing the properties of the generalized canonical transformation of the Birkhoffian system the solution of the problem can be obtained.The proposed method reveals the inherent relationship between the solution of a free Birkhoffian system and that of a constrained Birkhoffian system. The research results are of universal significance which can be further used in a variety of constrained mechanical systems such as non-conservative systems and nonholonomic systems etc.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11272050,11202090,11472124,11572034,and 11572145)the Science and Technology Research Project of Liaoning Province,China(Grant No.L2013005)+1 种基金China Postdoctoral Science Foundation(Grant No.2014M560203)the Doctor Start-up Fund in Liaoning Province of China(Grant No.20141050)
文摘It is a difficult problem to study the stability of the rheonomic and nonholonomic mechanical systems. Especially it is difficult to construct the Lyapunov function directly from the differential equation. But the gradient system is exactly suitable to study the stability of a dynamical system with the aid of the Lyapunov function. The stability of the solution for a simple rheonomic nonholonomic constrained system is studied in this paper. Firstly, the differential equations of motion of the system are established. Secondly, a problem in which the generalized forces are exerted on the system such that the solution is stable is proposed. Finally, the stable solutions of the rheonomic nonholonomic system can be constructed by using the gradient systems.
基金This work was supported by Beijing Science Foundation of the People's Republie of China.
文摘In this paper the generalized Bianchi's identities for the variant constrained system (GBIVOS)w ith non-invariant action integral and constraint conditions was derived, and the strong and weak conservation laws for such system was deduced. The preliminary applications of the GBIVCS to the case for some models of field theories was given. The Dirac constraint of such system was discussed.
基金Supported by National Natural Science Foundation of China under Grant Nos.11047020 and 11047173Natural Science Foundation of Shandong Province,China under Grant Nos.ZR2011AM019,ZR2010AQ025,BS2010DS006,and Y200814Scientific and Technological Development Projection of Shandong Province,China under Grant No.J08LI56
文摘We discuss the stationarity of generator G for gauge symmetries in two directions.One is to the motion equations defined by total Hamiltonian H T,and gives that the number of the independent coefficients in the generator G is not greater than the number of the primary first-class constraints,and the number of Noether conserved charges is not greater than that of the primary first-class constraints,too.The other is to the variances of canonical variables deduced from the generator G,and gives the variances of Lagrangian multipliers contained in extended Hamiltonian H E.And a second-class constraint generated by a first-class constraint may imply a new first-class constraint which can be combined by introducing other second-class constraints.Finally,we supply two examples.One with three first-class constraints(two is primary and one is secondary) has two Noether conserved charges,and the secondary first-class constraint is combined by three second-class constraints which are a secondary and two primary second-class constraints.The other with two first-class constraints(one is primary and one is secondary) has one Noehter conserved charge.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金supported in part by the Natural Sciences and Engineering Research Council of Canada(NSERC)supported by the National Natural Science Foundation of China under Grant 62303403Zhejiang Provincial Natural Science Foundation of China under Grants LR25F030004 and LQ24F030022。
文摘Switched systems play an imperative role in modeling many real industrial systems with abrupt changes.Due to possible exposure to unreliable and complex physical environments,switching dynamics may simultaneously face multiple faults,including the unexpected controller disconnect,the temporary mismatch between subsystems and desired corresponding controllers,and the intermittent disordering of mode transitions.These commonly arising faults may result in severe and detrimental impacts on the reliability and convergence of the closed-loop solution,thereby bringing significant yet challenging issues to be tackled.This paper provides the first attempt to investigate the stabilization problem for a class of constrained switched linear systems with multiple faults under mode-dependent dwell time(MDT).From a set-theory perspective,we demonstrate a critical necessary and sufficient stability condition for switched systems without uncertainties.Moreover,the non-conservative stability criterion is further extended to the perturbed switched systems with rigorous proof.A switching communication network example verifies the validity of the theoretical result and demonstrates their advantages.
基金Project(2022YFC2904502)supported by the National Key Research and Development Program of ChinaProject(62273357)supported by the National Natural Science Foundation of China。
文摘The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.
基金support through his Master scholarshipThe Vicerrectoría de Investigación y Estudios de Posgrado(VIEP-BUAP)partially funded this work under grant number 00593-PV/2025.
文摘This paper aims to fuse two well-established and,at the same time,opposed control techniques,namely,model predictive control(MPC)and active disturbance rejection control(ADRC),to develop a dynamic motion controller for a laser beam steering system.The proposed technique uses the ADRC philosophy to lump disturbances and model uncertainties into a total disturbance.Then,the total disturbance is estimated via a discrete extended state disturbance observer(ESO),and it is used to(1)handle the system constraints in a quadratic optimization problem and(2)injected as a feedforward term to the plant to reject the total disturbance,together with the feedback term obtained by the MPC.The main advantage of the proposed approach is that the MPC is designed based on a straightforward integrator-chain model such that a simple convex optimization problem is performed.Several experiments show the real-time closed-loop performance regarding trajectory tracking and disturbance rejection.Owing to simplicity,the self-contained approach MPC+ESO becomes a Frugal MPC,which is computationally economical,adaptable,efficient,resilient,and suitable for applications where on-board computational resources are limited.
基金Supported by the National Natural Science Foundation of China (12172241, 12272248)the Qing Lan Project of Colleges and Universities in Jiangsu Province。
文摘Singular systems within combined fractional derivatives are established.Firstly,the fractional Lagrange equation is analyzed.Secondly,the fractional primary constraint is given.Thirdly,the Noether and Lie symmetry methods of fractional constrained Hamiltonian system are studied.Finally,the obtained results are illustrated with an example.
基金supported in part by the National Natural Science Foundation of China(51939001,61976033,62273072)the Natural Science Foundation of Sichuan Province (2022NSFSC0903)。
文摘This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.
文摘This article presents an event-triggered H_(∞) consensus control scheme using reinforcement learning (RL) for nonlinear second-order multi-agent systems (MASs) with control constraints. First, considering control constraints, the constrained H_(∞) consensus problem is transformed into a multi-player zero-sum game with non-quadratic performance functions. Then, an event-triggered control method is presented to conserve communication resources and a new triggering condition is developed for each agent to make the triggering threshold independent of the disturbance attenuation level. To derive the optimal controller that can minimize the cost function in the case of worst disturbance, a constrained Hamilton–Jacobi–Bellman (HJB) equation is defined. Since it is difficult to solve analytically due to its strongly non-linearity, reinforcement learning (RL) is implemented to obtain the optimal controller. In specific, the optimal performance function and the worst-case disturbance are approximated by a time-triggered critic network;meanwhile, the optimal controller is approximated by event-triggered actor network. After that, Lyapunov analysis is utilized to prove the uniformly ultimately bounded (UUB) stability of the system and that the network weight errors are UUB. Finally, a simulation example is utilized to demonstrate the effectiveness of the control strategy provided.
基金National Natural Science Foundation of China(No.52373281)National Energy-Saving and Low-Carbon Materials Production and Application Demonstration Platform Program,China(No.TC220H06N)。
文摘The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical output still remains a significant challenge.Here,a strategy of inducing constrained phase separation on single nanofibers via shear force was proposed.Employing electrospinning technology,a polyacrylonitrile/polyvinylidene difluoride(PAN/PVDF)nanofibrous membrane was fabricated in one step,which enabled simultaneous piezoelectric and triboelectric conversion within a single-layer membrane.Each nanofiber contained independent components of PAN and PVDF and exhibited a rough surface.The abundant frictional contact points formed between these heterogeneous components contributed to an enhanced endogenous triboelectric output,showcasing an excellent synergistic effect of piezoelectric and triboelectric response in the nanofibrous membrane.Additionally,the component mass ratio influenced the microstructure,piezoelectric conformation and piezoelectric performance of the PAN/PVDF nanofibrous membranes.Through comprehensive performance comparison,the optimal mass ratio of PAN to PVDF was determined to be 9∶1.The piezoelectric devices made of the optimal PAN/PVDF nanofibrous membranes with rough nanofiber surfaces generated an output voltage of 20 V,which was about 1.8 times that of the smooth one at the same component mass ratio.The strategy of constrained phase separation on the surface of individual nanofibers provides a new approach to enhance the output performance of single-layer piezoelectric nanofibrous materials.
基金supported by the National Natural Science Foundation of China(62073094)the Fundamental Research Funds for the Central Universities(3072024GH0404)
文摘Dear Editor,This letter addresses the formation control problem for constrained underactuated autonomous underwater vehicles (AUVs). The feasibility condition of the virtual control law is eliminated by introducing a nonlinear state dependence function (NSDF) that transforms the state of each AUV in the formation.
基金supported by the National Natural Science Foundation of China(Nos.42530801,42425208)the Natural Science Foundation of Hubei Province(China)(No.2023AFA001)+1 种基金the MOST Special Fund from State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(No.MSFGPMR2025-401)the China Scholarship Council(No.202306410181)。
文摘Geochemical survey data are essential across Earth Science disciplines but are often affected by noise,which can obscure important geological signals and compromise subsequent prediction and interpretation.Quantifying prediction uncertainty is hence crucial for robust geoscientific decision-making.This study proposes a novel deep learning framework,the Spatially Constrained Variational Autoencoder(SC-VAE),for denoising geochemical survey data with integrated uncertainty quantification.The SC-VAE incorporates spatial regularization,which enforces spatial coherence by modeling inter-sample relationships directly within the latent space.The performance of the SC-VAE was systematically evaluated against a standard Variational Autoencoder(VAE)using geochemical data from the gold polymetallic district in the northwestern part of Sichuan Province,China.Both models were optimized using Bayesian optimization,with objective functions specifically designed to maintain essential geostatistical characteristics.Evaluation metrics include variogram analysis,quantitative measures of spatial interpolation accuracy,visual assessment of denoised maps,and statistical analysis of data distributions,as well as decomposition of uncertainties.Results show that the SC-VAE achieves superior noise suppression and better preservation of spatial structure compared to the standard VAE,as demonstrated by a significant reduction in the variogram nugget effect and an increased partial sill.The SC-VAE produces denoised maps with clearer anomaly delineation and more regularized data distributions,effectively mitigating outliers and reducing kurtosis.Additionally,it delivers improved interpolation accuracy and spatially explicit uncertainty estimates,facilitating more reliable and interpretable assessments of prediction confidence.The SC-VAE framework thus provides a robust,geostatistically informed solution for enhancing the quality and interpretability of geochemical data,with broad applicability in mineral exploration,environmental geochemistry,and other Earth Science domains.
基金supported by the National Natural Science Foundation of China(Grant No.12274117)the Natural Science Foundation of Henan(Grant No.242300421214)+4 种基金the Program for Innovative Research Team(in Science and Technology)in the University of Henan Province(Grant No.24IRTSTHN025)the Open Fund of Guangdong Provincial Key Laboratory of Nanophotonic Manipulation(No.202502)Guangdong S&T Program(No.2023B1212010008)the High-Performance Computing Center of Henan Normal Universitysupported by the U.S.DOE,Office of Science(Grant No.DE-FG02-05ER46237)。
文摘Altermagnetism,a recently identified class of collinear magnetism,combines key features of antiferromagnets and ferromagnets.Despite having zero net magnetization,altermagnetic materials exhibit anomalous transport effects,including the anomalous Hall,Nernst,and thermal Hall effects,as well as magneto-optical Kerr and Faraday effects.These phenomena,previously thought unique to ferromagnets,are dictated by symmetry,as confirmed by density functional theory(DFT)calculations.However,an effective model-based approach to verify these symmetry constraints remains unavailable.In this Letter,we construct a k·ρ model for d-wave altermagnets CuX_(2)(X=F,Cl)using spin space group representations and apply it to calculate the anomalous Hall effect.The symmetry-imposed transport properties predicted by the model are in agreement with the DFT results,providing a foundation for further investigation into symmetry-restricted transport phenomena in altermagnetic materials.
基金supported by the Intelligent Policing Key Laboratory of Sichuan Province(No.ZNJW2022KFZD002)This work was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202302403,KJQN202303111).
文摘Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.
基金supported in part by the National Key Research and Development Program of China(2022ZD0120001)the National Natural Science Foundation of China(62233004,62273090,62073076)the Jiangsu Provincial Scientific Research Center of Applied Mathematics(BK20233002)
文摘This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into account recent progress and addressing these concerns separately, there remains a lack of solutions offering theoretical guarantees for both privacy protection and constrained ZOO over time-varying unbalanced graphs.We hereby propose a novel algorithm, termed the differential privacy(DP) distributed push-sum based zeroth-order constrained optimization algorithm(DP-ZOCOA). Operating over time-varying unbalanced graphs, DP-ZOCOA obviates the need for supplemental suboptimization problem computations, thereby reducing overhead in comparison to distributed primary-dual methods. DP-ZOCOA is specifically tailored to tackle constrained ZOO problems over time-varying unbalanced graphs,offering a guarantee of convergence to the optimal solution while robustly preserving privacy. Moreover, we provide rigorous proofs of convergence and privacy for DP-ZOCOA, underscoring its efficacy in attaining optimal convergence without constraints. To enhance its applicability, we incorporate DP-ZOCOA into the federated learning framework and formulate a decentralized zeroth-order constrained federated learning algorithm(ZOCOA-FL) to address challenges stemming from the timevarying imbalance of communication topology. Finally, the performance and effectiveness of the proposed algorithms are thoroughly evaluated through simulations on distributed least squares(DLS) and decentralized federated learning(DFL) tasks.
文摘Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.
文摘This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.
文摘To reduce the number of the level sets used in algorithm of constrained nonlinear systems via ellipsoidal techniques, according to the analysis of mathematics, searching algorithm is used for choosing the control input. Simulation shows that the number of level sets used for controlling is almost the same as that used in polytope techniques. Sub time optimal algorithm reduces the number of the level sets used in ellipsoidal techniques.
基金The National Natural Science Foundation of China(No.10972151,11272227)
文摘For an in-depth study on the integration problem of the constrained mechanical systems the method of integration for the Birkhoffian system with constraints is discussed and the method of variation of parameters for solving the dynamical equations of the constrained Birkhoffian system is provided.First the differential equations of motion for the constrained Birkhoffian system as well as for the corresponding free Birkhoffian system are established.Secondly a system of auxiliary equations is constructed and the general solution of the equations is found.Finally by varying the parameters and utilizing the properties of the generalized canonical transformation of the Birkhoffian system the solution of the problem can be obtained.The proposed method reveals the inherent relationship between the solution of a free Birkhoffian system and that of a constrained Birkhoffian system. The research results are of universal significance which can be further used in a variety of constrained mechanical systems such as non-conservative systems and nonholonomic systems etc.
