Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynam...The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.展开更多
To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public i...To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public is constructed.The operation period is divided into different stages for differentiated analysis.A simulation analysis was performed on the Lituo sinking section of the Beijing-Hong Kong-Macao Highway to assess the impact of variations in critical elements on the system.The results indicate that the Lituo sinking section of the Beijing-Hong Kong-Macao Highway is currently in its early stage of development,with the corresponding strategies being active regulation,excessive emissions,and supervision.When the cost of the government’s active regulation decreases from 1×10^(5) to 5×10^(4) yuan,the system converges more rapidly toward the active regulation strategy.When the cost of the operator’s excessive emissions increases from 14.08×10^(6) to 20.00×10^(6) yuan,the system drives the operator toward the standardized emission strategy.In addition,when the cost of public supervision decreases from 15×10^(4) to 5×10^(4) yuan and the compensation paid by operators to the public increases from 1.288×10^(6) to 2.576×10^(6) yuan,the system converges more quickly toward the supervision strategy.The cost of the operator’s excessive emissions serves as the core decision variable for achieving the ideal equilibrium in the three-party game involving government active regulation,operator standardized emissions,and public supervision.展开更多
Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluct...Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.展开更多
CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voir...CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voirs.However,the use of these gels in high-temperature CCUS applications is limited due to their rever-sible swelling behavior at elevated temperatures.In this study,a novel dispersed particle gel(DPG)suspension is developed for high-temperature profile control in CCUS applications.First,we synthesize a double-network hydrogel consisting of a crosslinked polyacrylamide(PAAm)network and a crosslinked sodium alginate(SA)network.The hydrogel is then sheared in water to form a pre-prepared DPG suspen-sion.To enhance its performance,the gel particles are modified by introducing potassium methylsilan-etriolate(PMS)upon CO_(2) exposure.Comparing the particle size distributions of the modified and pre-prepared DPG suspension reveals a significant swelling of gel particles,over twice their original size.Moreover,subjecting the new DPG suspension to a 100℃ environment for 24 h demonstrates that its gel particle sizes do not decrease,confirming irreversible swelling,which is a significant advantage over the traditional CO_(2)-responsive gels.Thermogravimetric analysis further indicates improved thermal sta-bility compared to the pre-prepared DPG particles.Core flooding experiments show that the new DPG suspension achieves a high plugging efficiency of 95.3%in plugging an ultra-high permeability sandpack,whereas the pre-prepared DPG suspension achieves only 82.8%.With its high swelling ratio,irreversible swelling at high temperatures,enhanced thermal stability,and superior plugging performance,the newly developed DPG suspension in this work presents a highly promising solution for profile control in high-temperature CCUS applications.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mos...Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mosquitoes through vaccination.Using Culex pipiens(C.pipiens)as a model,we demonstrated that polyclonal antibodies against C.pipiens abdominal protein extracts significantly impaired oviposition and increased mosquito mortality,primarily through the classical complement activation pathways.However,repeated exposure led to resistance,indicating potential adaptation.Proteomic analysis identified metabolic proteins as key targets,with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses highlighting their roles in carboxylic acid metabolism,tyrosine degradation,and the proteasome pathways.Notably,cross-species reactivity was revealed by Western blotting,showing strong binding of Culex-specific antibodies to Anopheles and Aedes abdominal proteins.This study provides mechanistic insights into antibody-based mosquito suppression,highlighting its potential as an innovative vector control strategy while underscoring the need for further research on resistance management and ecological impacts.展开更多
This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow con...This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.展开更多
The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel ma...The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR(Susceptible-Exposed-Infectious-Recovered)framework to incorporate treatment and hospitalization compartments.The population is divided into eight compartments,with infectious individuals further categorized into influenza infectious,corona infectious,and co-infection cases.The proposed mathematical model is constrained to adhere to fundamental epidemiological properties,such as non-negativity and boundedness within a feasible region.Additionally,the model is demonstrated to be well-posed with a unique solution.Equilibrium points,including the disease-free and endemic equilibria,are identified,and various properties related to these equilibrium points,such as the basic reproduction number,are determined.Local and global sensitivity analyses are performed to identify the parameters that highly influence disease dynamics and the reproduction number.Knowing the most influential parameters is crucial for understanding their impact on the co-infection’s spread and severity.Furthermore,an optimal control problem is defined to minimize disease transmission and to control strategy costs.The purpose of our study is to identify the most effective(optimal)control strategies for mitigating the spread of the co-infection with minimum cost of the controls.The results illustrate the effectiveness of the implemented control strategies in managing the co-infection’s impact on the population’s health.This mathematical modeling and control strategy framework provides valuable tools for understanding and combating the dual threat of corona and influenza co-infection,helping public health authorities and policymakers make informed decisions in the face of these intertwined epidemics.展开更多
In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a lar...In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.展开更多
For optimization algorithms,the most important consideration is their global optimization performance.Our research is conducted with the hope that the algorithm can robustly find the optimal solution to the target pro...For optimization algorithms,the most important consideration is their global optimization performance.Our research is conducted with the hope that the algorithm can robustly find the optimal solution to the target problem at a lower computational cost or faster speed.For stochastic optimization algorithms based on population search methods,the search speed and solution quality are always contradictory.Suppose that the random range of the group search is larger;in that case,the probability of the algorithm converging to the global optimal solution is also greater,but the search speed will inevitably slow.The smaller the random range of the group search is,the faster the search speed will be,but the algorithm will easily fall into local optima.Therefore,our method is intended to utilize heuristic strategies to guide the search direction and extract as much effective information as possible from the search process to guide an optimized search.This method is not only conducive to global search,but also avoids excessive randomness,thereby improving search efficiency.To effectively avoid premature convergence problems,the diversity of the group must be monitored and regulated.In fact,in natural bird flocking systems,the distribution density and diversity of groups are often key factors affecting individual behavior.For example,flying birds can adjust their speed in time to avoid collisions based on the crowding level of the group,while foraging birds will judge the possibility of sharing food based on the density of the group and choose to speed up or escape.The aim of this work was to verify that the proposed optimization method is effective.We compared and analyzed the performances of five algorithms,namely,self-organized particle swarm optimization(PSO)-diversity controlled inertia weight(SOPSO-DCIW),self-organized PSO-diversity controlled acceleration coefficient(SOPSO-DCAC),standard PSO(SPSO),the PSO algorithm with a linear decreasing inertia weight(SPSO-LDIW),and the modified PSO algorithm with a time-varying acceleration constant(MPSO-TVAC).展开更多
The exploitation of durable and highly active Pt-based electrocatalysts for the oxygen reduction reaction(ORR)is essential for the commercialization of proton exchange membrane fuel cells(PEMFCs).Herein,we designed Pt...The exploitation of durable and highly active Pt-based electrocatalysts for the oxygen reduction reaction(ORR)is essential for the commercialization of proton exchange membrane fuel cells(PEMFCs).Herein,we designed Pt@Pt_(3)Ti core-shell nanoparticles with atomic-controllable shells through precise thermal diffusing Ti into Pt nanoparticles for effective and durable ORR.Combining theoretical and experiment analysis,we found that the lattice strain of Pt_(3)Ti shells can be tailored by precisely controlling the thick-ness of Pt_(3)Ti shell in atomic-scale on account of the lattice constant difference between Pt and Pt_(3)Ti to optimize adsorption properties of Pt_(3)Ti for ORR intermediates,thus enhancing its performance.The Pt@Pt_(3)Ti catalyst with one-atomic Pt_(3)Ti shell(Pt@1L-Pt_(3)Ti/TiO_(2)-C)demonstrates excellent performance with mass activity of 592 mA mgpt-1 and durability nearly 19.5-fold that of commercial Pt/C with negligible decay(2%)after 30,000 potential cycles(0.6-1.0 V vs.RHE).Notably,at higher potential cycles(1.0 V-1.5 V vs.RHE),Pt@1L-Pt_(3)Ti/TiO_(2)-C also showed far superior durability than Pt/C(9.6%decayed while 54.8% for commercial Pt/C).This excellent stability is derived from the intrinsic stability of Pt_(3)Ti alloy and the confinement effect of TiO_(2)-C.The catalyst's enhancement was further confirmed in PEMFC configuration.展开更多
The application of plant measurement data for system identification and model predictive control(MPC)has garnered significant interest.However,the pervasive presence of noise and contamination in industrial data often...The application of plant measurement data for system identification and model predictive control(MPC)has garnered significant interest.However,the pervasive presence of noise and contamination in industrial data often compromises data quality,thereby degrading performance and reliability of model.To address this challenge,this study proposes a nonlinear MPC method based on robust time delay particle filtering(RPF-MPC).This method is specifically designed to mitigate the impact of stochastic time delays and noise on both model learning and control.RPF-MPC utilizes robust particle filtering with a Laplace distribution to reliably estimate parameters and unknown time delays.In this way,the controller is able to efficiently handle noise and outliers even when the data deviates from a Gaussian distribution.The proposed algorithm is presented in detail,a nonlinear numerical case and a fuel cell water cooling control case are presented to validate the effectiveness of the RPF-MPC method.Simulation results validate the effectiveness and robustness of the RPF-MPC method in handling uncertainty and improving control performance in the PEMFC process.展开更多
This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the i...This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the impact of wakes on turbine effective wind speed is analyzed,leading to a quantitative method for assessing wake interactions.Based on these interactions,a partitioning method divides the wind farm into smaller,computationally manageable zones.Subsequently,a heuristic control algorithm is developed for yaw optimization within each partition,reducing the overall computational burden associated with multi-turbine optimization.The algorithm’s effectiveness is evaluated through case studies on 11-turbine and 28-turbine wind farms,demonstrating power generation increases of 9.78%and 1.78%,respectively,compared to baseline operation.The primary innovation lies in coupling the higher-fidelity dynamic FLORIDyn wake model with a graph-based partitioning strategy and a computationally efficient heuristic optimization,enabling scalable and accurate yaw control for large wind farms,overcoming limitations associated with simplified models or centralized optimization approaches.展开更多
This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to es...This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs.Secondly,the unknown parameter linearly associated with control input is acquired by the adaptive control approach,and a discrete time extended state observer is designed to estimate nonlinear uncertainties.Thirdly,in order to achieve the prescribed performance,the constrained bipartite consensus error is transformed through a strictly increasing function.Based on the converted equivalent unconstrained error function,a sliding mode controller using only the input and output data of the MASs is designed.Finally,the efficacy of the controller is confirmed by simulations.展开更多
In this article,we study the approximate controllability of neutral partial differential equations with Hilfer fractional derivative and not instantaneous impulses effects.By using the Sadovskii's fixed point theo...In this article,we study the approximate controllability of neutral partial differential equations with Hilfer fractional derivative and not instantaneous impulses effects.By using the Sadovskii's fixed point theorem,fractional calculus and resolvent operator functions,we prove the approximate controllability of the considered system.展开更多
To understand the applicability of high-temperature preformed particle gel(HT-PPG)for control of short-circuiting in enhanced geothermal systems(EGSs),core flooding experiments were conducted on fractured granite core...To understand the applicability of high-temperature preformed particle gel(HT-PPG)for control of short-circuiting in enhanced geothermal systems(EGSs),core flooding experiments were conducted on fractured granite cores under varying fracture widths,gel particle sizes and swelling ratios.Key parameters such as injection pressure,water breakthrough pressure,and residual resistance factor were measured to evaluate HT-PPG performance.The gel exhibited strong injectability,entering granite fractures at pressure gradients as low as 0.656 MPa/m;HT-PPG yields a superior sealing performance by significantly reducing the permeability;and dehydration occurs during HT-PPG propagation,with a dehydration ratio ranging from 4.71%to 11.36%.This study reveals that HT-PPG can be injected into geothermal formations with minimal pressure yet provides strong resistance to breakthrough once in place.This balance of injectability and sealing strength makes HT-PPG effective for addressing thermal short-circuiting in EGS reservoirs.展开更多
Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybr...Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.展开更多
Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to...Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to the restricted sets.Then,the proposed scheme is extended to the case of single-qudit operations.As long as the controller and the higher-layer senders consent,the receiver can restore the desired state remotely operated by the sender.It is worth mentioning that the recovery operation is deduced by general formulas which clearly reveal the relationship with the measurement outcomes.For the sake of clarity,two specific examples with two levels are given respectively.In addition,we discuss the influence of amplitude-damping noise and utilize weak measurement and measurement reversal to effectively resist noise.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金National Natural Science Foundation of China(No.12071370)。
文摘The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.
基金The Natural Science Foundation of Heilongjiang Province(No.LH2023E011)Open Fund of National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment in Changsha University of Science and Technology(No.kfj230105).
文摘To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public is constructed.The operation period is divided into different stages for differentiated analysis.A simulation analysis was performed on the Lituo sinking section of the Beijing-Hong Kong-Macao Highway to assess the impact of variations in critical elements on the system.The results indicate that the Lituo sinking section of the Beijing-Hong Kong-Macao Highway is currently in its early stage of development,with the corresponding strategies being active regulation,excessive emissions,and supervision.When the cost of the government’s active regulation decreases from 1×10^(5) to 5×10^(4) yuan,the system converges more rapidly toward the active regulation strategy.When the cost of the operator’s excessive emissions increases from 14.08×10^(6) to 20.00×10^(6) yuan,the system drives the operator toward the standardized emission strategy.In addition,when the cost of public supervision decreases from 15×10^(4) to 5×10^(4) yuan and the compensation paid by operators to the public increases from 1.288×10^(6) to 2.576×10^(6) yuan,the system converges more quickly toward the supervision strategy.The cost of the operator’s excessive emissions serves as the core decision variable for achieving the ideal equilibrium in the three-party game involving government active regulation,operator standardized emissions,and public supervision.
基金supported by the National Natural Science Foundation of China(Project No.52377082)the Scientific Research Program of Jilin Provincial Department of Education(Project No.JJKH20230123KJ).
文摘Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.
基金Lin Du acknowledges the financial support provided by China Scholarship Council(CSC)via a Ph.D.Scholarship(202008510128)supported by Core Technology Project of China National Petroleum Corporation(CNPC)"Research on Thermal Miscible Flooding Technology"(2023ZG18)。
文摘CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voirs.However,the use of these gels in high-temperature CCUS applications is limited due to their rever-sible swelling behavior at elevated temperatures.In this study,a novel dispersed particle gel(DPG)suspension is developed for high-temperature profile control in CCUS applications.First,we synthesize a double-network hydrogel consisting of a crosslinked polyacrylamide(PAAm)network and a crosslinked sodium alginate(SA)network.The hydrogel is then sheared in water to form a pre-prepared DPG suspen-sion.To enhance its performance,the gel particles are modified by introducing potassium methylsilan-etriolate(PMS)upon CO_(2) exposure.Comparing the particle size distributions of the modified and pre-prepared DPG suspension reveals a significant swelling of gel particles,over twice their original size.Moreover,subjecting the new DPG suspension to a 100℃ environment for 24 h demonstrates that its gel particle sizes do not decrease,confirming irreversible swelling,which is a significant advantage over the traditional CO_(2)-responsive gels.Thermogravimetric analysis further indicates improved thermal sta-bility compared to the pre-prepared DPG particles.Core flooding experiments show that the new DPG suspension achieves a high plugging efficiency of 95.3%in plugging an ultra-high permeability sandpack,whereas the pre-prepared DPG suspension achieves only 82.8%.With its high swelling ratio,irreversible swelling at high temperatures,enhanced thermal stability,and superior plugging performance,the newly developed DPG suspension in this work presents a highly promising solution for profile control in high-temperature CCUS applications.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Natural Science Foundation of China(Grant No.82472312).
文摘Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mosquitoes through vaccination.Using Culex pipiens(C.pipiens)as a model,we demonstrated that polyclonal antibodies against C.pipiens abdominal protein extracts significantly impaired oviposition and increased mosquito mortality,primarily through the classical complement activation pathways.However,repeated exposure led to resistance,indicating potential adaptation.Proteomic analysis identified metabolic proteins as key targets,with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses highlighting their roles in carboxylic acid metabolism,tyrosine degradation,and the proteasome pathways.Notably,cross-species reactivity was revealed by Western blotting,showing strong binding of Culex-specific antibodies to Anopheles and Aedes abdominal proteins.This study provides mechanistic insights into antibody-based mosquito suppression,highlighting its potential as an innovative vector control strategy while underscoring the need for further research on resistance management and ecological impacts.
基金the Scientific Research Projects Unit of Erciyes University under contract no:FDS-2022-11532 and FOA-2025-14773.
文摘This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.
基金supported by NASA Oklahoma Established Program to Stimulate Competitive Research(EPSCoR)Infrastructure Development,“Machine Learning Ocean World Biosignature Detection from Mass Spec”(PI:BrettMcKinney),Grant No.80NSSC24M0109Tandy School of Computer Science,University of Tulsa.
文摘The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR(Susceptible-Exposed-Infectious-Recovered)framework to incorporate treatment and hospitalization compartments.The population is divided into eight compartments,with infectious individuals further categorized into influenza infectious,corona infectious,and co-infection cases.The proposed mathematical model is constrained to adhere to fundamental epidemiological properties,such as non-negativity and boundedness within a feasible region.Additionally,the model is demonstrated to be well-posed with a unique solution.Equilibrium points,including the disease-free and endemic equilibria,are identified,and various properties related to these equilibrium points,such as the basic reproduction number,are determined.Local and global sensitivity analyses are performed to identify the parameters that highly influence disease dynamics and the reproduction number.Knowing the most influential parameters is crucial for understanding their impact on the co-infection’s spread and severity.Furthermore,an optimal control problem is defined to minimize disease transmission and to control strategy costs.The purpose of our study is to identify the most effective(optimal)control strategies for mitigating the spread of the co-infection with minimum cost of the controls.The results illustrate the effectiveness of the implemented control strategies in managing the co-infection’s impact on the population’s health.This mathematical modeling and control strategy framework provides valuable tools for understanding and combating the dual threat of corona and influenza co-infection,helping public health authorities and policymakers make informed decisions in the face of these intertwined epidemics.
基金supported in part by the National Natural Science Foundation of China(62473142,62203161)Special Funding Support for the Construction of Innovative Provinces in Hunan Province(2021GK1010)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2024A1515011579),Project of State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle(72275007).
文摘In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.
文摘For optimization algorithms,the most important consideration is their global optimization performance.Our research is conducted with the hope that the algorithm can robustly find the optimal solution to the target problem at a lower computational cost or faster speed.For stochastic optimization algorithms based on population search methods,the search speed and solution quality are always contradictory.Suppose that the random range of the group search is larger;in that case,the probability of the algorithm converging to the global optimal solution is also greater,but the search speed will inevitably slow.The smaller the random range of the group search is,the faster the search speed will be,but the algorithm will easily fall into local optima.Therefore,our method is intended to utilize heuristic strategies to guide the search direction and extract as much effective information as possible from the search process to guide an optimized search.This method is not only conducive to global search,but also avoids excessive randomness,thereby improving search efficiency.To effectively avoid premature convergence problems,the diversity of the group must be monitored and regulated.In fact,in natural bird flocking systems,the distribution density and diversity of groups are often key factors affecting individual behavior.For example,flying birds can adjust their speed in time to avoid collisions based on the crowding level of the group,while foraging birds will judge the possibility of sharing food based on the density of the group and choose to speed up or escape.The aim of this work was to verify that the proposed optimization method is effective.We compared and analyzed the performances of five algorithms,namely,self-organized particle swarm optimization(PSO)-diversity controlled inertia weight(SOPSO-DCIW),self-organized PSO-diversity controlled acceleration coefficient(SOPSO-DCAC),standard PSO(SPSO),the PSO algorithm with a linear decreasing inertia weight(SPSO-LDIW),and the modified PSO algorithm with a time-varying acceleration constant(MPSO-TVAC).
基金supported by the National Natural Science Foundation of China(No.21875039)the Project on the Integration of Industry-Education-Research of Fujian Province(No.2021H6020)the State Key Laboratory of Advanced Technology for Materials Synthesis and Processing(Wuhan University of Technology).
文摘The exploitation of durable and highly active Pt-based electrocatalysts for the oxygen reduction reaction(ORR)is essential for the commercialization of proton exchange membrane fuel cells(PEMFCs).Herein,we designed Pt@Pt_(3)Ti core-shell nanoparticles with atomic-controllable shells through precise thermal diffusing Ti into Pt nanoparticles for effective and durable ORR.Combining theoretical and experiment analysis,we found that the lattice strain of Pt_(3)Ti shells can be tailored by precisely controlling the thick-ness of Pt_(3)Ti shell in atomic-scale on account of the lattice constant difference between Pt and Pt_(3)Ti to optimize adsorption properties of Pt_(3)Ti for ORR intermediates,thus enhancing its performance.The Pt@Pt_(3)Ti catalyst with one-atomic Pt_(3)Ti shell(Pt@1L-Pt_(3)Ti/TiO_(2)-C)demonstrates excellent performance with mass activity of 592 mA mgpt-1 and durability nearly 19.5-fold that of commercial Pt/C with negligible decay(2%)after 30,000 potential cycles(0.6-1.0 V vs.RHE).Notably,at higher potential cycles(1.0 V-1.5 V vs.RHE),Pt@1L-Pt_(3)Ti/TiO_(2)-C also showed far superior durability than Pt/C(9.6%decayed while 54.8% for commercial Pt/C).This excellent stability is derived from the intrinsic stability of Pt_(3)Ti alloy and the confinement effect of TiO_(2)-C.The catalyst's enhancement was further confirmed in PEMFC configuration.
基金supported by Jianbing Lingyan Foundation of Zhejiang Province,China(2023C01022)Major Project of Science and Technology of Yunnan Province(202402AD080001)Zhejiang University-China Tobacco Zhejiang Industrial Joint Laboratory Project。
文摘The application of plant measurement data for system identification and model predictive control(MPC)has garnered significant interest.However,the pervasive presence of noise and contamination in industrial data often compromises data quality,thereby degrading performance and reliability of model.To address this challenge,this study proposes a nonlinear MPC method based on robust time delay particle filtering(RPF-MPC).This method is specifically designed to mitigate the impact of stochastic time delays and noise on both model learning and control.RPF-MPC utilizes robust particle filtering with a Laplace distribution to reliably estimate parameters and unknown time delays.In this way,the controller is able to efficiently handle noise and outliers even when the data deviates from a Gaussian distribution.The proposed algorithm is presented in detail,a nonlinear numerical case and a fuel cell water cooling control case are presented to validate the effectiveness of the RPF-MPC method.Simulation results validate the effectiveness and robustness of the RPF-MPC method in handling uncertainty and improving control performance in the PEMFC process.
基金supported by the Science and Technology Project of China South Power Grid Co.,Ltd.under Grant No.036000KK52222044(GDKJXM20222430).
文摘This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn(FLOW Redirection and Induction Dynamics)dynamic wake model.First,the impact of wakes on turbine effective wind speed is analyzed,leading to a quantitative method for assessing wake interactions.Based on these interactions,a partitioning method divides the wind farm into smaller,computationally manageable zones.Subsequently,a heuristic control algorithm is developed for yaw optimization within each partition,reducing the overall computational burden associated with multi-turbine optimization.The algorithm’s effectiveness is evaluated through case studies on 11-turbine and 28-turbine wind farms,demonstrating power generation increases of 9.78%and 1.78%,respectively,compared to baseline operation.The primary innovation lies in coupling the higher-fidelity dynamic FLORIDyn wake model with a graph-based partitioning strategy and a computationally efficient heuristic optimization,enabling scalable and accurate yaw control for large wind farms,overcoming limitations associated with simplified models or centralized optimization approaches.
基金supported in part by the National Natural Science Foundation of China(62373113,62433014,62433018)the Guangdong Basic and Applied Basic Research Foundation(2023A1515011527,2023B1515120010).Recommended by Associate Editor Xiaohua Ge。
文摘This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs.Secondly,the unknown parameter linearly associated with control input is acquired by the adaptive control approach,and a discrete time extended state observer is designed to estimate nonlinear uncertainties.Thirdly,in order to achieve the prescribed performance,the constrained bipartite consensus error is transformed through a strictly increasing function.Based on the converted equivalent unconstrained error function,a sliding mode controller using only the input and output data of the MASs is designed.Finally,the efficacy of the controller is confirmed by simulations.
基金Supported by Shandong University of Finance and Economics 2023 International Collaborative Projectsthe National Natural Science Foundation of China(Grant No.62073190)。
文摘In this article,we study the approximate controllability of neutral partial differential equations with Hilfer fractional derivative and not instantaneous impulses effects.By using the Sadovskii's fixed point theorem,fractional calculus and resolvent operator functions,we prove the approximate controllability of the considered system.
基金Supported by the U.S.Department of Energy’s Office of Energy Efficiency and Renewable Energy(EERE)under the Geothermal Technologies Office(GTO)“Innovative Methods to Control Hydraulic Properties of Enhanced Geothermal Systems”(DE-EE0009790).
文摘To understand the applicability of high-temperature preformed particle gel(HT-PPG)for control of short-circuiting in enhanced geothermal systems(EGSs),core flooding experiments were conducted on fractured granite cores under varying fracture widths,gel particle sizes and swelling ratios.Key parameters such as injection pressure,water breakthrough pressure,and residual resistance factor were measured to evaluate HT-PPG performance.The gel exhibited strong injectability,entering granite fractures at pressure gradients as low as 0.656 MPa/m;HT-PPG yields a superior sealing performance by significantly reducing the permeability;and dehydration occurs during HT-PPG propagation,with a dehydration ratio ranging from 4.71%to 11.36%.This study reveals that HT-PPG can be injected into geothermal formations with minimal pressure yet provides strong resistance to breakthrough once in place.This balance of injectability and sealing strength makes HT-PPG effective for addressing thermal short-circuiting in EGS reservoirs.
文摘Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.
基金supported by the National Natural Science Foundation of China(Grant Nos.62172341,12071132)the Natural Science Foundation of Henan Province of China(Grant No.242300420276)the Joint Fund of Henan Province Science and Technology R&D Program(Grant No.225200810032)。
文摘Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to the restricted sets.Then,the proposed scheme is extended to the case of single-qudit operations.As long as the controller and the higher-layer senders consent,the receiver can restore the desired state remotely operated by the sender.It is worth mentioning that the recovery operation is deduced by general formulas which clearly reveal the relationship with the measurement outcomes.For the sake of clarity,two specific examples with two levels are given respectively.In addition,we discuss the influence of amplitude-damping noise and utilize weak measurement and measurement reversal to effectively resist noise.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
