Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs ...Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.展开更多
High intermittence of renewable energy resources(RESs)and restriction for greenhouse gas(GHG)emissions have significantly challenged the operations of traditional diesel generator(DG)based microgirds.This paper consid...High intermittence of renewable energy resources(RESs)and restriction for greenhouse gas(GHG)emissions have significantly challenged the operations of traditional diesel generator(DG)based microgirds.This paper considers an emission-free microgid with hybrid hydrogen-battery energy storage(HHBES)and proposes a coordinated operational strategy to minimize its daily operation costs.In addition to the electricity purchase costs in the day-ahead market and the operational costs of RESs,the total degradation cost of HHBES is also included in the cost calculation.The proposed operational strategy consists of two coordinated stages.At the day-ahead stage,the schedule for the tie-line power is exchanged with the main grid,the output power of the fuel cell(FC)and the input power of the electrolysis device(ED)are optimized under the worst case of uncertain power output from RESs and power demand from electricity loads(ELs).At the intra-day stage,the battery power is determined according to the short-term prediction for the power of RESs and ELs.The problem is formulated as a robust optimization model and solved by a two-level column-andconstraint-generation(C&CG)algorithm.Numerical simulations using Australian energy market operator(AEMO)data are carried out to validate the effectiveness of the proposed strategy.展开更多
Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently...Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.展开更多
Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the s...Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.展开更多
Thermally conductive papers with electrical insulation and mechanical robustness are essential for efficient thermal management in modern electronics.In this study,we introduced a metal ion-assisted interfacial crossl...Thermally conductive papers with electrical insulation and mechanical robustness are essential for efficient thermal management in modern electronics.In this study,we introduced a metal ion-assisted interfacial crosslinking strategy to strengthen sugarfunctionalized graphene fluoride(SGF)and cellulose nanofibers(CNF)by hydrogen bonding and metal ion crosslinking that leads to simultaneous enhancements in thermal conductivity and mechanical properties.The facile sugarassisted ball-milling exfoliation method was developed to achieve the exfoliation of graphite fluoride and hydroxyl group functionalization on the surface of graphene fluoride.Thanks to the good dispersibility of the SGF sheets in water,the flexible SGF/CNF composite papers with hydrogen bonding were prepared via vacuum-assisted filtration.We introduced hydrogen bonding and metal ion crosslinking into SGF/CNF papers to obtain densely packed composite papers.Ca^(2+)or Al^(3+)ion-crosslinked SGF/CNF papers exhibited superior thermal and mechanical properties owing to hydrogen bonding and metal ion crosslinking.SGF/CNF-Ca^(2+)and SGF/CNF-Al^(3+)papers at 50 wt%of SGF yield in-plane thermal conductivities of 72.93 and 75.02 W m^(-1) K^(-1),and tensile strengths of 121.5 and 135.7 MPa,respectively.A thermal percolation value was observed at 12.6 vol%of SGF filler content.In addition,the SGF/CNF papers exhibited electrical insulation properties.These remarkable characteristics of the metal ion-crosslinked SGF/CNF papers are attributed to the densely packed structures caused by the strong interfacial interactions from hydrogen bonding as well as metal ion-crosslinking that could promote phonon transport.High-performance metal ion-crosslinked SGF/CNF papers with these fascinating advantages offer great potential for the thermal management of flexible electronics.展开更多
Mn-based layered oxides(KMO)have emerged as one of the promising low-cost cathodes for potassiumion batteries(PIBs).However,due to the multiple-phase transitions and the distortion in the MnO6structure induced by the ...Mn-based layered oxides(KMO)have emerged as one of the promising low-cost cathodes for potassiumion batteries(PIBs).However,due to the multiple-phase transitions and the distortion in the MnO6structure induced by the Jahn-Teller(JT)effect associated with Mn-ion,the cathode exhibits poor structural stability.Herein,we propose a strategy to enhance structural stability by introducing robust metal-oxygen(M-O)bonds,which can realize the pinning effect to constrain the distortion in the transition metal(TM)layer.Concurrently,all the elements employed have exceptionally high crustal abundance.As a proof of concept,the designed K_(0.5)Mn_(0.9)Mg_(0.025)Ti_(0.025)Al_(0.05)O_(2)cathode exhibited a discharge capacity of approximately 100 mA h g^(-1)at 20 mA g^(-1)with 79%capacity retention over 50 cycles,and 73%capacity retention over 200 cycles at 200 mA g^(-1),showcased much better battery performance than the designed cathode with less robust M-O bonds.The properties of the formed M-O bonds were investigated using theoretical calculations.The enhanced dynamics,mitigated JT effect,and improved structural stability were elucidated through the in-situ X-ray diffractometer(XRD),in-situ electrochemical impedance spectroscopy(EIS)(and distribution of relaxation times(DRT)method),and ex-situ X-ray absorption fine structure(XAFS)tests.This study holds substantial reference value for the future design of costeffective Mn-based layered cathodes for PIBs.展开更多
To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distrib...To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.展开更多
Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resi...Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resistant to intentional or unintentional modification.Some of these features are important perceptual features according to the human visual system(HVS),which means that the embedded watermark should be imperceptible in these features.Therefore,both the designers of watermarking algorithms and potential attackers must consider these perceptual features when carrying out their actions.The two roles will be considered in this paper when designing a robust watermarking algorithm against the most harmful attacks,like volumetric scaling,histogram equalization,and non-conventional watermarking attacks like the Denoising Convolution Neural Network(DnCNN),which must be considered in watermarking algorithm design due to its rising role in the state-of-the-art attacks.The DnCNN is initialized and trained using watermarked image samples created by our proposed Covert and Severe Attacks Resistant Watermarking Algorithm(CSRWA)to prove its robustness.For this algorithm to satisfy the robustness and imperceptibility tradeoff,implementing the Dither Modulation(DM)algorithm is boosted by utilizing the Just Noticeable Distortion(JND)principle to get an improved performance in this sense.Sensitivity,luminance,inter and intra-block contrast are used to adjust the JND values.展开更多
Incremental Nonlinear Dynamic Inversion(INDI)is a control approach that has gained popularity in flight control over the past decade.Besides the INDI law,several common additional components complement an INDI-based c...Incremental Nonlinear Dynamic Inversion(INDI)is a control approach that has gained popularity in flight control over the past decade.Besides the INDI law,several common additional components complement an INDI-based controller.This paper,the second part of a two-part series of surveys on INDI,aims to summarize the modern trends in INDI and its related components.Besides a comprehensive components specification,it addresses their most common challenges,compares different variants,and discusses proposed advances.Further important aspects of INDI are gain design,stability,and robustness.This paper also provides an overview of research conducted concerning these aspects.This paper is written in a tutorial style to familiarize researchers with the essential specifics and pitfalls of INDI and its components.At the same time,it can also serve as a reference for readers already familiar with INDI.展开更多
Advances in software and hardware technologies have facilitated the production of quadrotor unmanned aerial vehicles(UAVs).Nowadays,people actively use quadrotor UAVs in essential missions such as search and rescue,co...Advances in software and hardware technologies have facilitated the production of quadrotor unmanned aerial vehicles(UAVs).Nowadays,people actively use quadrotor UAVs in essential missions such as search and rescue,counter-terrorism,firefighting,surveillance,and cargo transportation.While performing these tasks,quadrotors must operate in noisy environments.Therefore,a robust controller design that can control the altitude and attitude of the quadrotor in noisy environments is of great importance.Many researchers have focused only on white Gaussian noise in their studies,whereas researchers need to consider the effects of all colored noises during the operation of the quadrotor.This study aims to design a robust controller that is resistant to all colored noises.Firstly,a nonlinear quadrotormodel was created with MATLAB.Then,a backstepping controller resistant to colored noises was designed.Thedesigned backstepping controller was tested under Gaussian white,pink,brown,blue,and purple noises.PID and Lyapunov-based controller designswere also carried out,and their time responses(rise time,overshoot,settling time)were compared with those of the backstepping controller.In the simulations,time was in seconds,altitude was in meters,and roll,pitch,and yaw references were in radians.Rise and settling time values were in seconds,and overshoot value was in percent.When the obtained values are examined,simulations prove that the proposed backstepping controller has the least overshoot and the shortest settling time under all noise types.展开更多
Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist mo...Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist model uncertainties between the nominal model and the real robot manipulator and disturbances. Hence, dealing with their effects plays a crucial role in leading to high tracking performances, as discussed in [1]–[5].展开更多
While in the past the robustness of transportation networks was studied considering the cyber and physical space as isolated environments this is no longer the case.Integrating the Internet of Things devices in the se...While in the past the robustness of transportation networks was studied considering the cyber and physical space as isolated environments this is no longer the case.Integrating the Internet of Things devices in the sensing area of transportation infrastructure has resulted in ubiquitous cyber-physical systems and increasing interdependen-cies between the physical and cyber networks.As a result,the robustness of transportation networks relies on the uninterrupted serviceability of physical and cyber networks.Current studies on interdependent networks overlook the civil engineering aspect of cyber-physical systems.Firstly,they rely on the assumption of a uniform and strong level of interdependency.That is,once a node within a network fails its counterpart fails immedi-ately.Current studies overlook the impact of earthquake and other natural hazards on the operation of modern transportation infrastructure,that now serve as a cyber-physical system.The last is responsible not only for the physical operation(e.g.,flow of vehicles)but also for the continuous data transmission and subsequently the cy-ber operation of the entire transportation network.Therefore,the robustness of modern transportation networks should be modelled from a new cyber-physical perspective that includes civil engineering aspects.In this paper,we propose a new robustness assessment approach for modern transportation networks and their underlying in-terdependent physical and cyber network,subjected to earthquake events.The novelty relies on the modelling of interdependent networks,in the form of a graph,based on their interdependency levels.We associate the service-ability level of the coupled physical and cyber network with the damage states induced by earthquake events.Robustness is then measured as a degradation of the cyber-physical serviceability level.The application of the approach is demonstrated by studying an illustrative transportation network using seismic data from real-world transportation infrastructure.Furthermore,we propose the integration of a robustness improvement indicator based on physical and cyber attributes to enhance the cyber-physical serviceability level.Results indicate an improvement in robustness level(i.e.,41%)by adopting the proposed robustness improvement indicator.The usefulness of our approach is highlighted by comparing it with other methods that consider strong interdepen-dencies and key node protection strategies.The approach is of interest to stakeholders who are attempting to incorporate cyber-physical systems into civil engineering systems.展开更多
Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or...Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or eliminate the effects of these uncertainties.However,the robustness to uncertainties of electrical drive systems has not been clearly defined.No systemic procedures have been proposed to evaluate a control system's robustness(how robust it is).This paper proposes a systemic method for evaluating control systems'robustness to uncertainties.The concept and fundamental theory of robust control are illustrated by considering a simple uncertain feedback control system.The effects of uncertainties on the control performance and stability are analyzed and discussed.The concept of design for six-sigma(a robust design method)is employed to numerically evaluate the robustness levels of control systems.To show the effectiveness of the proposed robustness evaluation method,case studies are conducted for second-order systems,DC motor drive systems,and PMSM drive systems.Besides the conventional predictive control of PMSM drive,three different robust predictive control methods are evaluated in terms of two different parametric uncertainty ranges and three application requirements against parametric uncertainties.展开更多
This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in tradition...This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.展开更多
Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi meth...Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi methods in optimizing diverse energy systems.While previous reviews have focused on these methods separately,this paper presents the first integrated analysis of both approaches across multiple energy applications.We systematically analyze their implementation in:Internal combustion engines,Thermal energy storage systems,Solar energy systems,Wind and tidal turbines,Heat exchangers,and hybrid energy systems.Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90%when compared to experimental data,while Taguchi-based methods combined with Grey Relational Analysis(GRA)or TOPSIS can improve system performance by up to 20%30%in multi-objective optimization scenarios.The review introduces novel frameworks for combining these methods and provides critical insights into their complementary strengths.Key statistical metrics,including determination coefficients and error analyses,validate the superior performance of integrated approaches.This work serves as a foundational reference for researchers and practitioners in energy system optimization,offering structured methodologies and future research directions.展开更多
Superhydrophobic glass has inspiring development prospects in endoscopes,solar panels and other engineering and medical fields.However,the surface topography required to achieve superhydrophobicity will inevitably aff...Superhydrophobic glass has inspiring development prospects in endoscopes,solar panels and other engineering and medical fields.However,the surface topography required to achieve superhydrophobicity will inevitably affect the surface transparency and limit the application of glass materials.To resolve the contradiction between the surface transparency and the robust superhydrophobicity,an efficient and low-cost laser-chemical surface functionalization process was utilized to fabricate superhydrophobic glass surface.The results show that the air can be effectively trapped in surface micro/nanostructure induced by laser texturing,thus reducing the solid-liquid contact area and interfacial tension.The deposition of hydrophobic carbon-containing groups on the surface can be accelerated by chemical treatment,and the surface energy is significantly reduced.The glass surface exhibits marvelous robust superhydrophobicity with a contact angle of 155.8°and a roll-off angle of 7.2°under the combination of hierarchical micro/nanostructure and low surface energy.Moreover,the surface transparency of the prepared superhydrophobic glass was only 5.42%lower than that of the untreated surface.This superhydrophobic glass with high transparency still maintains excellent superhydrophobicity after durability and stability tests.The facile fabrication of superhydrophobic glass with high transparency and robustness provides a strong reference for further expanding the application value of glass materials.展开更多
Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of softwar...Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of software systems have attracted a tremendous amount of interest in recent years.In this paper,based on the source code of Tar and MySQL,we propose an approach to generate coupled software networks and construct three kinds of directed software networks:The function call network,the weakly coupled network and the strongly coupled network.The structural properties of these complex networks are extensively investigated.It is found that the average influence and the average dependence for all functions are the same.Moreover,eight attacking strategies and two robustness indicators(the weakly connected indicator and the strongly connected indicator)are introduced to analyze the robustness of software networks.This shows that the strongly coupled network is just a weakly connected network rather than a strongly connected one.For MySQL,high in-degree strategy outperforms other attacking strategies when the weakly connected indicator is used.On the other hand,high out-degree strategy is a good choice when the strongly connected indicator is adopted.This work will highlight a better understanding of the structure and robustness of software networks.展开更多
Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission sche...Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI)is proposed.To model CSI uncertainty,an expectation-based error model is utilized.The main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation.The problem is formulated as a combinatorial optimization problem and is solved in two steps.First,the priority order of devices is determined by a sparsity-inducing procedure.Then,a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met.An alternating optimization(AO)scheme is used to transform the resulting nonconvex problem into two convex subproblems.Numerical results illustrate the effectiveness and robustness of the proposed scheme.展开更多
Federated learning(FL)is a distributed machine learning paradigm that excels at preserving data privacy when using data from multiple parties.When combined with Fog Computing,FL offers enhanced capabilities for machin...Federated learning(FL)is a distributed machine learning paradigm that excels at preserving data privacy when using data from multiple parties.When combined with Fog Computing,FL offers enhanced capabilities for machine learning applications in the Internet of Things(IoT).However,implementing FL across large-scale distributed fog networks presents significant challenges in maintaining privacy,preventing collusion attacks,and ensuring robust data aggregation.To address these challenges,we propose an Efficient Privacy-preserving and Robust Federated Learning(EPRFL)scheme for fog computing scenarios.Specifically,we first propose an efficient secure aggregation strategy based on the improved threshold homomorphic encryption algorithm,which is not only resistant to model inference and collusion attacks,but also robust to fog node dropping.Then,we design a dynamic gradient filtering method based on cosine similarity to further reduce the communication overhead.To minimize training delays,we develop a dynamic task scheduling strategy based on comprehensive score.Theoretical analysis demonstrates that EPRFL offers robust security and low latency.Extensive experimental results indicate that EPRFL outperforms similar strategies in terms of privacy preserving,model performance,and resource efficiency.展开更多
基金Project(2002CB312200) supported by the National Key Fundamental Research and Development Program of China project(60574019) supported by the National Natural Science Foundation of China
文摘Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.
基金The work was supported in part by T-RECs Energy Pte.Ltd.under Grand No.04IDS000719N014the National Natural Science Foundation of China(71801054)。
文摘High intermittence of renewable energy resources(RESs)and restriction for greenhouse gas(GHG)emissions have significantly challenged the operations of traditional diesel generator(DG)based microgirds.This paper considers an emission-free microgid with hybrid hydrogen-battery energy storage(HHBES)and proposes a coordinated operational strategy to minimize its daily operation costs.In addition to the electricity purchase costs in the day-ahead market and the operational costs of RESs,the total degradation cost of HHBES is also included in the cost calculation.The proposed operational strategy consists of two coordinated stages.At the day-ahead stage,the schedule for the tie-line power is exchanged with the main grid,the output power of the fuel cell(FC)and the input power of the electrolysis device(ED)are optimized under the worst case of uncertain power output from RESs and power demand from electricity loads(ELs).At the intra-day stage,the battery power is determined according to the short-term prediction for the power of RESs and ELs.The problem is formulated as a robust optimization model and solved by a two-level column-andconstraint-generation(C&CG)algorithm.Numerical simulations using Australian energy market operator(AEMO)data are carried out to validate the effectiveness of the proposed strategy.
基金National Natural Science Foundation of China(11971211,12171388).
文摘Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.
基金supported in part by the National Natural Science Foundation of China under Grant 52077002。
文摘Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.
基金supported by the Basic Science Program(No.2022R1A2C2009700)through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICTthe Basic Science Research Capacity Enhancement Project(National Research Facilities and Equipment Center)through the Korea Ba-sic Science Institute funded by the Ministry of Education(No.2019R1A6C1010047)the Industrial Strategic Technology Development Program(No.20013248)through Korea Evaluation In-stitute of Industrial Technology funded by the Ministry of Trade,Industry&Energy(MOTIE,Korea).
文摘Thermally conductive papers with electrical insulation and mechanical robustness are essential for efficient thermal management in modern electronics.In this study,we introduced a metal ion-assisted interfacial crosslinking strategy to strengthen sugarfunctionalized graphene fluoride(SGF)and cellulose nanofibers(CNF)by hydrogen bonding and metal ion crosslinking that leads to simultaneous enhancements in thermal conductivity and mechanical properties.The facile sugarassisted ball-milling exfoliation method was developed to achieve the exfoliation of graphite fluoride and hydroxyl group functionalization on the surface of graphene fluoride.Thanks to the good dispersibility of the SGF sheets in water,the flexible SGF/CNF composite papers with hydrogen bonding were prepared via vacuum-assisted filtration.We introduced hydrogen bonding and metal ion crosslinking into SGF/CNF papers to obtain densely packed composite papers.Ca^(2+)or Al^(3+)ion-crosslinked SGF/CNF papers exhibited superior thermal and mechanical properties owing to hydrogen bonding and metal ion crosslinking.SGF/CNF-Ca^(2+)and SGF/CNF-Al^(3+)papers at 50 wt%of SGF yield in-plane thermal conductivities of 72.93 and 75.02 W m^(-1) K^(-1),and tensile strengths of 121.5 and 135.7 MPa,respectively.A thermal percolation value was observed at 12.6 vol%of SGF filler content.In addition,the SGF/CNF papers exhibited electrical insulation properties.These remarkable characteristics of the metal ion-crosslinked SGF/CNF papers are attributed to the densely packed structures caused by the strong interfacial interactions from hydrogen bonding as well as metal ion-crosslinking that could promote phonon transport.High-performance metal ion-crosslinked SGF/CNF papers with these fascinating advantages offer great potential for the thermal management of flexible electronics.
基金financially supported by the National Natural Science Foundation of China(NSFC)(52274295)the Natural Science Foundation of Hebei Province(E2021501029)+3 种基金the Fundamental Research Funds for the Central Universities(N2423051,N2423053,N2302016,N2423019,N2323013,N2423005)the Science and Technology Project of Hebei Education Department(QN2024238)the Basic Research Program Project of Shijiazhuang City for Universities Stationed in Hebei Province(241790937A)the Science and Technology Project of Qinhuangdao City in 2023.
文摘Mn-based layered oxides(KMO)have emerged as one of the promising low-cost cathodes for potassiumion batteries(PIBs).However,due to the multiple-phase transitions and the distortion in the MnO6structure induced by the Jahn-Teller(JT)effect associated with Mn-ion,the cathode exhibits poor structural stability.Herein,we propose a strategy to enhance structural stability by introducing robust metal-oxygen(M-O)bonds,which can realize the pinning effect to constrain the distortion in the transition metal(TM)layer.Concurrently,all the elements employed have exceptionally high crustal abundance.As a proof of concept,the designed K_(0.5)Mn_(0.9)Mg_(0.025)Ti_(0.025)Al_(0.05)O_(2)cathode exhibited a discharge capacity of approximately 100 mA h g^(-1)at 20 mA g^(-1)with 79%capacity retention over 50 cycles,and 73%capacity retention over 200 cycles at 200 mA g^(-1),showcased much better battery performance than the designed cathode with less robust M-O bonds.The properties of the formed M-O bonds were investigated using theoretical calculations.The enhanced dynamics,mitigated JT effect,and improved structural stability were elucidated through the in-situ X-ray diffractometer(XRD),in-situ electrochemical impedance spectroscopy(EIS)(and distribution of relaxation times(DRT)method),and ex-situ X-ray absorption fine structure(XAFS)tests.This study holds substantial reference value for the future design of costeffective Mn-based layered cathodes for PIBs.
基金supported by State Grid Anhui Electric Power Co.,Ltd.Research Program(B3120923000C).
文摘To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.
文摘Watermarking is embedding visible or invisible data within media to verify its authenticity or protect copyright.The watermark is embedded in significant spatial or frequency features of the media to make it more resistant to intentional or unintentional modification.Some of these features are important perceptual features according to the human visual system(HVS),which means that the embedded watermark should be imperceptible in these features.Therefore,both the designers of watermarking algorithms and potential attackers must consider these perceptual features when carrying out their actions.The two roles will be considered in this paper when designing a robust watermarking algorithm against the most harmful attacks,like volumetric scaling,histogram equalization,and non-conventional watermarking attacks like the Denoising Convolution Neural Network(DnCNN),which must be considered in watermarking algorithm design due to its rising role in the state-of-the-art attacks.The DnCNN is initialized and trained using watermarked image samples created by our proposed Covert and Severe Attacks Resistant Watermarking Algorithm(CSRWA)to prove its robustness.For this algorithm to satisfy the robustness and imperceptibility tradeoff,implementing the Dither Modulation(DM)algorithm is boosted by utilizing the Just Noticeable Distortion(JND)principle to get an improved performance in this sense.Sensitivity,luminance,inter and intra-block contrast are used to adjust the JND values.
文摘Incremental Nonlinear Dynamic Inversion(INDI)is a control approach that has gained popularity in flight control over the past decade.Besides the INDI law,several common additional components complement an INDI-based controller.This paper,the second part of a two-part series of surveys on INDI,aims to summarize the modern trends in INDI and its related components.Besides a comprehensive components specification,it addresses their most common challenges,compares different variants,and discusses proposed advances.Further important aspects of INDI are gain design,stability,and robustness.This paper also provides an overview of research conducted concerning these aspects.This paper is written in a tutorial style to familiarize researchers with the essential specifics and pitfalls of INDI and its components.At the same time,it can also serve as a reference for readers already familiar with INDI.
文摘Advances in software and hardware technologies have facilitated the production of quadrotor unmanned aerial vehicles(UAVs).Nowadays,people actively use quadrotor UAVs in essential missions such as search and rescue,counter-terrorism,firefighting,surveillance,and cargo transportation.While performing these tasks,quadrotors must operate in noisy environments.Therefore,a robust controller design that can control the altitude and attitude of the quadrotor in noisy environments is of great importance.Many researchers have focused only on white Gaussian noise in their studies,whereas researchers need to consider the effects of all colored noises during the operation of the quadrotor.This study aims to design a robust controller that is resistant to all colored noises.Firstly,a nonlinear quadrotormodel was created with MATLAB.Then,a backstepping controller resistant to colored noises was designed.Thedesigned backstepping controller was tested under Gaussian white,pink,brown,blue,and purple noises.PID and Lyapunov-based controller designswere also carried out,and their time responses(rise time,overshoot,settling time)were compared with those of the backstepping controller.In the simulations,time was in seconds,altitude was in meters,and roll,pitch,and yaw references were in radians.Rise and settling time values were in seconds,and overshoot value was in percent.When the obtained values are examined,simulations prove that the proposed backstepping controller has the least overshoot and the shortest settling time under all noise types.
基金support by “R&D Program for Forest Science Technology(RS-2024-0040 3460)” provided by Korea Forest Service(Korea Forestry Promotion Institute)
文摘Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist model uncertainties between the nominal model and the real robot manipulator and disturbances. Hence, dealing with their effects plays a crucial role in leading to high tracking performances, as discussed in [1]–[5].
文摘While in the past the robustness of transportation networks was studied considering the cyber and physical space as isolated environments this is no longer the case.Integrating the Internet of Things devices in the sensing area of transportation infrastructure has resulted in ubiquitous cyber-physical systems and increasing interdependen-cies between the physical and cyber networks.As a result,the robustness of transportation networks relies on the uninterrupted serviceability of physical and cyber networks.Current studies on interdependent networks overlook the civil engineering aspect of cyber-physical systems.Firstly,they rely on the assumption of a uniform and strong level of interdependency.That is,once a node within a network fails its counterpart fails immedi-ately.Current studies overlook the impact of earthquake and other natural hazards on the operation of modern transportation infrastructure,that now serve as a cyber-physical system.The last is responsible not only for the physical operation(e.g.,flow of vehicles)but also for the continuous data transmission and subsequently the cy-ber operation of the entire transportation network.Therefore,the robustness of modern transportation networks should be modelled from a new cyber-physical perspective that includes civil engineering aspects.In this paper,we propose a new robustness assessment approach for modern transportation networks and their underlying in-terdependent physical and cyber network,subjected to earthquake events.The novelty relies on the modelling of interdependent networks,in the form of a graph,based on their interdependency levels.We associate the service-ability level of the coupled physical and cyber network with the damage states induced by earthquake events.Robustness is then measured as a degradation of the cyber-physical serviceability level.The application of the approach is demonstrated by studying an illustrative transportation network using seismic data from real-world transportation infrastructure.Furthermore,we propose the integration of a robustness improvement indicator based on physical and cyber attributes to enhance the cyber-physical serviceability level.Results indicate an improvement in robustness level(i.e.,41%)by adopting the proposed robustness improvement indicator.The usefulness of our approach is highlighted by comparing it with other methods that consider strong interdepen-dencies and key node protection strategies.The approach is of interest to stakeholders who are attempting to incorporate cyber-physical systems into civil engineering systems.
文摘Numerous uncertainties in practical production and operation can seriously affect the drive performance of permanent magnet synchronous machines(PMSMs).Various robust control methods have been developed to mitigate or eliminate the effects of these uncertainties.However,the robustness to uncertainties of electrical drive systems has not been clearly defined.No systemic procedures have been proposed to evaluate a control system's robustness(how robust it is).This paper proposes a systemic method for evaluating control systems'robustness to uncertainties.The concept and fundamental theory of robust control are illustrated by considering a simple uncertain feedback control system.The effects of uncertainties on the control performance and stability are analyzed and discussed.The concept of design for six-sigma(a robust design method)is employed to numerically evaluate the robustness levels of control systems.To show the effectiveness of the proposed robustness evaluation method,case studies are conducted for second-order systems,DC motor drive systems,and PMSM drive systems.Besides the conventional predictive control of PMSM drive,three different robust predictive control methods are evaluated in terms of two different parametric uncertainty ranges and three application requirements against parametric uncertainties.
基金Supported by National Natural Science Foundation of China(Grant Nos.52025121,52394263)National Key R&D Plan of China(Grant No.2023YFD2000301)+2 种基金Foundation of State Key Laboratory of Automobile Safety and Energy Saving of China(Grant No.KFZ2201)the Jiangsu Provincial Scientific Research Center of Applied Mathematics under(Grant No.BK20233002)Special Fund of Jiangsu Province for the Transformation of Scientific and Technological Achievements under(Grant No.BA2021023)。
文摘This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.
文摘Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi methods in optimizing diverse energy systems.While previous reviews have focused on these methods separately,this paper presents the first integrated analysis of both approaches across multiple energy applications.We systematically analyze their implementation in:Internal combustion engines,Thermal energy storage systems,Solar energy systems,Wind and tidal turbines,Heat exchangers,and hybrid energy systems.Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90%when compared to experimental data,while Taguchi-based methods combined with Grey Relational Analysis(GRA)or TOPSIS can improve system performance by up to 20%30%in multi-objective optimization scenarios.The review introduces novel frameworks for combining these methods and provides critical insights into their complementary strengths.Key statistical metrics,including determination coefficients and error analyses,validate the superior performance of integrated approaches.This work serves as a foundational reference for researchers and practitioners in energy system optimization,offering structured methodologies and future research directions.
基金Projects(52105175,52305149)supported by the National Natural Science Foundation of ChinaProject(2242024RCB0035)supported by the Zhishan Young Scholar Program of Southeast University,China+5 种基金Project(BK20210235)supported by the Natural Science Foundation of Jiangsu Province,ChinaProject(2023MK042)supported by the State Administration for Market Regulation,ChinaProject(KJ2023003)supported by the Jiangsu Administration for Market Regulation,ChinaProjects(KJ(Y)202429,KJ(YJ)2023001)supported by the Jiangsu Province Special Equipment Safety Supervision Inspection Institute,ChinaProject(JSSCBS20210121)supported by the Jiangsu Provincial Innovative and Entrepreneurial Doctor Program,ChinaProject(1102002310)supported by the Technology Innovation Project for Returnees in Nanjing,China。
文摘Superhydrophobic glass has inspiring development prospects in endoscopes,solar panels and other engineering and medical fields.However,the surface topography required to achieve superhydrophobicity will inevitably affect the surface transparency and limit the application of glass materials.To resolve the contradiction between the surface transparency and the robust superhydrophobicity,an efficient and low-cost laser-chemical surface functionalization process was utilized to fabricate superhydrophobic glass surface.The results show that the air can be effectively trapped in surface micro/nanostructure induced by laser texturing,thus reducing the solid-liquid contact area and interfacial tension.The deposition of hydrophobic carbon-containing groups on the surface can be accelerated by chemical treatment,and the surface energy is significantly reduced.The glass surface exhibits marvelous robust superhydrophobicity with a contact angle of 155.8°and a roll-off angle of 7.2°under the combination of hierarchical micro/nanostructure and low surface energy.Moreover,the surface transparency of the prepared superhydrophobic glass was only 5.42%lower than that of the untreated surface.This superhydrophobic glass with high transparency still maintains excellent superhydrophobicity after durability and stability tests.The facile fabrication of superhydrophobic glass with high transparency and robustness provides a strong reference for further expanding the application value of glass materials.
基金supported by the Beijing Education Commission Science and Technology Project(No.KM201811417005)the National Natural Science Foundation of China(No.62173237)+6 种基金the Aeronautical Science Foundation of China(No.20240055054001)the Open Fund of State Key Laboratory of Satellite Navigation System and Equipment Technology(No.CEPNT2023A01)Joint Fund of Ministry of Natural Resources Key Laboratory of Spatiotemporal Perception and Intelligent Processing(No.232203)the Civil Aviation Flight Technology and Flight Safety Engineering Technology Research Center of Sichuan(No.GY2024-02B)the Applied Basic Research Programs of Liaoning Province(No.2025JH2/101300011)the General Project of Liaoning Provincial Education Department(No.20250054)Research on Safety Intelligent Management Technology and Systems for Mixed Operations of General Aviation Aircraft in Low-Altitude Airspace(No.310125011).
文摘Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of software systems have attracted a tremendous amount of interest in recent years.In this paper,based on the source code of Tar and MySQL,we propose an approach to generate coupled software networks and construct three kinds of directed software networks:The function call network,the weakly coupled network and the strongly coupled network.The structural properties of these complex networks are extensively investigated.It is found that the average influence and the average dependence for all functions are the same.Moreover,eight attacking strategies and two robustness indicators(the weakly connected indicator and the strongly connected indicator)are introduced to analyze the robustness of software networks.This shows that the strongly coupled network is just a weakly connected network rather than a strongly connected one.For MySQL,high in-degree strategy outperforms other attacking strategies when the weakly connected indicator is used.On the other hand,high out-degree strategy is a good choice when the strongly connected indicator is adopted.This work will highlight a better understanding of the structure and robustness of software networks.
文摘Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI)is proposed.To model CSI uncertainty,an expectation-based error model is utilized.The main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation.The problem is formulated as a combinatorial optimization problem and is solved in two steps.First,the priority order of devices is determined by a sparsity-inducing procedure.Then,a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met.An alternating optimization(AO)scheme is used to transform the resulting nonconvex problem into two convex subproblems.Numerical results illustrate the effectiveness and robustness of the proposed scheme.
基金supported in part by the National Natural Science Foundation of China(62462053)the Science and Technology Foundation of Qinghai Province(2023-ZJ-731)+1 种基金the Open Project of the Qinghai Provincial Key Laboratory of Restoration Ecology in Cold Area(2023-KF-12)the Open Research Fund of Guangdong Key Laboratory of Blockchain Security,Guangzhou University。
文摘Federated learning(FL)is a distributed machine learning paradigm that excels at preserving data privacy when using data from multiple parties.When combined with Fog Computing,FL offers enhanced capabilities for machine learning applications in the Internet of Things(IoT).However,implementing FL across large-scale distributed fog networks presents significant challenges in maintaining privacy,preventing collusion attacks,and ensuring robust data aggregation.To address these challenges,we propose an Efficient Privacy-preserving and Robust Federated Learning(EPRFL)scheme for fog computing scenarios.Specifically,we first propose an efficient secure aggregation strategy based on the improved threshold homomorphic encryption algorithm,which is not only resistant to model inference and collusion attacks,but also robust to fog node dropping.Then,we design a dynamic gradient filtering method based on cosine similarity to further reduce the communication overhead.To minimize training delays,we develop a dynamic task scheduling strategy based on comprehensive score.Theoretical analysis demonstrates that EPRFL offers robust security and low latency.Extensive experimental results indicate that EPRFL outperforms similar strategies in terms of privacy preserving,model performance,and resource efficiency.
