This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynami...This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.展开更多
On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enha...On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.展开更多
Fuzzy control has shown success in some application areas and emerged as analternative to some conventional control schemes. There are also some drawbacks in this approach,for example it is hard to justify the choice ...Fuzzy control has shown success in some application areas and emerged as analternative to some conventional control schemes. There are also some drawbacks in this approach,for example it is hard to justify the choice of fuzzy controller parameters and control rules, andcontrol precision is low, and so on. Fuzzy control is developing towards self-learning and adaptive.The ship steering motion is a nonlinear, coupling, time-delay complicated system. How to control iteffectively is the problem that many scholars are studying. In this paper, based on the repeatedcontrol of the robot, the self-learning arithmetic was worked out. The arithmetic was realized infuzzy logic way and used in cargo steering. It is the first time for the arithmetic to be used incargo steering. Our simulation results show that the arithmetic is effective and has severalpotential advantages over conventional fuzzy control. This work lays a foundation in modeling andanalyzing the fuzzy learning control system.展开更多
This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the ...This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule, and to automatically generate fuzzy control actions under each condition. The dynamics of the controlled system is unknown to the GA. The only information for evaluating performance is a failure signal indicating that the controlled system is out of control. We compare its performance with that of other learning methods for the same problem. We also examine the ability of the algorithm to adapt to changing conditions. Simulation results show that such an approach for self-learning fuzzy control rules is both effective and robust.展开更多
This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globall...This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globally searching process of genetic algorithm, aiming to enhance the convergence rate and real-time learning ability of genetic algorithm, which is then used to construct fuzzy controllers for complex dynamic systems without any knowledge about system dynamics and prior control experience. The cart-pole system is employed as a test bed to demonstrate the effectiveness of the proposed control scheme, and the robustness of the acquired fuzzy controller with comparable result.展开更多
In this paper, the weld pool shape control by intelligent strategy was studied. A neuron self-learning PSD controller for backside width of weld pool in pulsed GTAW with wire filler was designed. The PSD control arith...In this paper, the weld pool shape control by intelligent strategy was studied. A neuron self-learning PSD controller for backside width of weld pool in pulsed GTAW with wire filler was designed. The PSD control arithmetic was analyzed, simulating experiment by MATLAB software was done, and the validating experiments on varied heat sink workpiece and varied gap workpiece were successfully implemented. The study results show that the neuron self-learning PSD control method can attain a perfect control effect under different set values and conditions, and is suitable for the welding process with the varied structure and coefficients of control model.展开更多
The weld pool shape control by intelligent strategy was studied. In order to improve the ability of self-learning and self-adaptation of the ordinary fuzzy control, a self-learning fuzzy neural network controller (FNN...The weld pool shape control by intelligent strategy was studied. In order to improve the ability of self-learning and self-adaptation of the ordinary fuzzy control, a self-learning fuzzy neural network controller (FNNC) for backside width of weld pool in pulsed gas tungsten arc welding (GTAW) with wire filler was designed. In FNNC, the fuzzy system was expressed by an equivalence neural network, the membership functions and inference rulers were decided through the learning of the neural network. Then, the FNNC control arithmetic was analyzed, simulating experiment was done, and the validating experiments on varied heat sink workpiece and varied gap workpiece were implemented. The maximum error between the real value and the given one was 0.39mm, the mean error was 0.014mm, and the root-mean-square was 0.14mm. The real backside width was maintained around the given value. The results show that the self-learning fuzzy neural network control strategy can achieve a perfect control effect under different set values and conditions, and is suitable for the welding process with the varied structure and coefficients of control model.展开更多
Human-machine cooperative control has become an important area of intelligent driving,where driver intention recognition and dynamic control authority allocation are key factors for improving the performance of cooper...Human-machine cooperative control has become an important area of intelligent driving,where driver intention recognition and dynamic control authority allocation are key factors for improving the performance of cooperative decision-making and control.In this paper,an online learning method is proposed for human-machine cooperative control,which introduces a priority control parameter in the reward function to achieve optimal allocation of control authority under different driver intentions and driving safety conditions.Firstly,a two-layer LSTM-based sequence prediction algorithm is proposed to recognise the driver's lane change(LC)intention for human-machine cooperative steering control.Secondly,an online reinforcement learning method is developed for optimising the steering authority to reduce driver workload and improve driving safety.The driver-in-the-loop simulation results show that our method can accurately predict the driver's LC intention in cooperative driving and effectively compensate for the driver's non-optimal driving actions.The experimental results on a real intelligent vehicle further demonstrate the online optimisation capability of the proposed RL-based control authority allocation algorithm and its effectiveness in improving driving safety.展开更多
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
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
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and ...As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and diverse communication needs.It is crucial to design control sequences with robust randomness and conflict-freeness to properly address differentiated access control in data link.In this paper,we propose a hierarchical access control scheme based on control sequences to achieve high utilization of time slots and differentiated access control.A theoretical bound of the hierarchical control sequence set is derived to characterize the constraints on the parameters of the sequence set.Moreover,two classes of optimal hierarchical control sequence sets satisfying the theoretical bound are constructed,both of which enable the scheme to achieve maximum utilization of time slots.Compared with the fixed time slot allocation scheme,our scheme reduces the symbol error rate by up to 9%,which indicates a significant improvement in anti-interference and eavesdropping capabilities.展开更多
In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regiona...In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regional controllability is more adapted to systems described by dynamic systems.Regional controllability results in a strategic area were established for vibrating plates by the Hilbertian Uniqueness Method.展开更多
Molten salt reactors,being the only reactor type among Generation Ⅳ advanced nuclear reactors that utilize liquid fuels,offer inherent safety,high-temperature,and low-pressure operation,as well as the capability for ...Molten salt reactors,being the only reactor type among Generation Ⅳ advanced nuclear reactors that utilize liquid fuels,offer inherent safety,high-temperature,and low-pressure operation,as well as the capability for online fuel reprocessing.However,the fuel-salt flow results in the decay of delayed neutron precursors(DNPs)outside the core,causing fluctuations in the effective delayed neutron fraction and consequently impacting the reactor reactivity.Particularly in accident scenarios—such as a combined pump shutdown and the inability to rapidly scram the reactor—the sole reliance on negative temperature feedback may cause a significant increase in core temperature,posing a threat to reactor safety.To address these problems,this paper introduces an innovative design for a passive fluid-driven suspended control rod(SCR)to dynamically compensate for reactivity fluctuations caused by DNPs flowing with the fuel.The control rod operates passively by leveraging the combined effects of gravity,buoyancy,and fluid dynamic forces,thereby eliminating the need for an external drive mechanism and enabling direct integration within the active region of the core.Using a 150 MWt thorium-based molten salt reactor as the reference design,we develop a mathematical model to systematically analyze the effects of key parameters—including the geometric dimensions and density of the SCR—on its performance.We examine its motion characteristics under different core flow conditions and assess its feasibility for the dynamic compensation of reactivity changes caused by fuel flow.The results of this study demonstrate that the SCR can effectively counteract reactivity fluctuations induced by fuel flow within molten salt reactors.A sensitivity analysis reveals that the SCR’s average density exerts a profound impact on its start-up flow threshold,channel flow rate,resistance to fuel density fluctuations,and response characteristics.This underscores the critical need to optimize this parameter.Moreover,by judiciously selecting the SCR’s length,number of deployed units,and the placement we can achieve the necessary reactivity control while maintaining a favorable balance between neutron economy and heat transfer performance.Ultimately,this paper provides an innovative solution for the passive reactivity control in molten salt reactors,offering significant potential for practical engineering applications.展开更多
Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressi...Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.展开更多
To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance dat...To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.展开更多
AIM:To investigate the effects of binocular fusional C-optotypes(positive/negative)and 2D planar C-optotypes on the amplitude and stability of transient accommodation(TAC)in adults,and to provide a basis for non-conta...AIM:To investigate the effects of binocular fusional C-optotypes(positive/negative)and 2D planar C-optotypes on the amplitude and stability of transient accommodation(TAC)in adults,and to provide a basis for non-contact myopia intervention.METHODS:This was a self-controlled study.Using redblue 3D technology,four experimental stages were set up:Test A[fixating on the 1 m negative fusional C-optotypes,8△base-in(BI)],Test B(fixating on the 5 m planar C-optotypes),Test C(fixating on the 1 m planar C-optotypes),and Test D[fixating on the 1 m positive fusional C-optotypes,20△base-out(BO)].A WAM-5500 open-field autorefractor was used to measure TAC and accommodative microfluctuations[evaluated via interquartile range(IQR)and median-based coefficient of variation(CVmed)].Additionally,the convergence accommodation to convergence(CA/C)ratio was calculated,and a visual fatigue questionnaire was administered to assess participants’subjective visual comfort.RESULTS:A total of 21 subjects(7 males,14 females;aged 23-41y)with normal binocular visual function were enrolled.The results showed that the TAC increased gradually across the four stages,and these values were Test A(-0.35±0.26 D)<Test B(-0.46±0.24 D)<Test C(-0.77±0.32 D)<Test D(-1.38±0.31 D).There were significant overall differences(F=56.136,P<0.001).Compared with Test C,Test A reduced TAC by 0.42 D(P<0.05),while Test D increased it by 0.61 D(P<0.001).There was no significant intergroup difference in accommodative fluctuation amplitude(all P>0.05),but the fluctuation stability of Test D showed a significant difference between the first 20s and the second 20s(P=0.017).The CA/C ratio was significantly higher in Test D(0.05±0.02 D/△)than in Test A(0.03±0.02 D/△,P=0.007),indicating stronger accommodation-convergence linkage during positive fusional fixation.The visual fatigue scores of all stages were low(median 0-1),with Test D slightly higher than Test B and Test C(P<0.05).No linear correlation was found between TAC and age(all r<0.1,P>0.05).CONCLUSION:Negative fusional C-optotypes induce ciliary muscle relaxation to reduce TAC,while positive fusional C-optotypes enhance accommodation-convergence coordination to increase TAC.The red-blue 3D-based noncontact training mode exhibits good safety(median visual fatigue scores:0-1 across all tests)and provides a novel dual-directional(relaxation-activation)strategy for myopia prevention and control.展开更多
Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-me...Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.展开更多
The concept of Damage Control Surgery(DCS)emphasizes prioritizing hemorrhage control,preventing hypothermia,correcting coagulopathy,and acidosis in trauma treatment.The application of the DCS concept in trauma treatme...The concept of Damage Control Surgery(DCS)emphasizes prioritizing hemorrhage control,preventing hypothermia,correcting coagulopathy,and acidosis in trauma treatment.The application of the DCS concept in trauma treatment at grassroots hospitals faces numerous challenges such as limited resources,high technical difficulty,and insufficient multidisciplinary collaboration.Therefore,DCS strategies need to be adapted to simplified processes to create conditions for subsequent treatment.This paper retrieves relevant literature to discuss the proposal,promotion,and application of the DCS concept,aiming to provide evidence-based basis for optimizing trauma treatment outcomes at grassroots hospitals.展开更多
Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering consi...Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering considerable potential for absorbing surplus power and enhancing grid flexibility.However,conventional control architectures typically treat the power converter and electrolyzer as independent units,neglecting their dynamic interactions and thereby limiting overall system performance under practical operating conditions.This review critically examines existing control approaches,ranging from classical proportional-integral schemes to model predictive control,fuzzy-logic algorithms,and data-driven methods,evaluating their effectiveness in managing dynamic response,multivariable coupling,and operational constraints as well as their inherent limitations.Attention is then focused on the performance requirements of the hydrogen-production converter,including current ripple suppression,rapid transient response,adaptive thermal regulation,and stable power delivery.An integrated co‑control framework is proposed,aligning converter output with electrolyzer demand across steady-state operation,variable renewable input,and emergency shutdown scenarios to achieve higher efficiency,extended equipment lifetime,and enhanced operational safety.Finally,prospects for advancing unified control methodologies are outlined,with emphasis on constraint-aware predictive control,machine-learning-enhanced modeling,and real‑time co‑optimization for future alkaline electrolyzer systems.展开更多
基金Supported by the National Science Foundation (U.S.A.) under Grant ECS-0355364
文摘This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.
基金Item Sponsored by National Natural Science Foundation of China (50527402)
文摘On the basis of a simulated bright continuous annealing experimental machine, a process control model for heating system was built. The heating model was simplified and self-learning parameters were normalized to enhance the precision of temperature control. By means of the division of temperature layers and the exponential smoothing disposal of the annealing experimental data, the self-learning of the heating model was carried out. Through exponentially smoothing the deviation of self-learning parameters of the heated phase in heating process, dynamic modifications of self-learning parameters and heating electric current were carried out, and the precision of temperature control was confirmed. The application indicated that the process control model for the heating system can control temperature with high precision, and the deviation can be controlled within 8 ℃.
文摘Fuzzy control has shown success in some application areas and emerged as analternative to some conventional control schemes. There are also some drawbacks in this approach,for example it is hard to justify the choice of fuzzy controller parameters and control rules, andcontrol precision is low, and so on. Fuzzy control is developing towards self-learning and adaptive.The ship steering motion is a nonlinear, coupling, time-delay complicated system. How to control iteffectively is the problem that many scholars are studying. In this paper, based on the repeatedcontrol of the robot, the self-learning arithmetic was worked out. The arithmetic was realized infuzzy logic way and used in cargo steering. It is the first time for the arithmetic to be used incargo steering. Our simulation results show that the arithmetic is effective and has severalpotential advantages over conventional fuzzy control. This work lays a foundation in modeling andanalyzing the fuzzy learning control system.
文摘This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule, and to automatically generate fuzzy control actions under each condition. The dynamics of the controlled system is unknown to the GA. The only information for evaluating performance is a failure signal indicating that the controlled system is out of control. We compare its performance with that of other learning methods for the same problem. We also examine the ability of the algorithm to adapt to changing conditions. Simulation results show that such an approach for self-learning fuzzy control rules is both effective and robust.
文摘This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globally searching process of genetic algorithm, aiming to enhance the convergence rate and real-time learning ability of genetic algorithm, which is then used to construct fuzzy controllers for complex dynamic systems without any knowledge about system dynamics and prior control experience. The cart-pole system is employed as a test bed to demonstrate the effectiveness of the proposed control scheme, and the robustness of the acquired fuzzy controller with comparable result.
文摘In this paper, the weld pool shape control by intelligent strategy was studied. A neuron self-learning PSD controller for backside width of weld pool in pulsed GTAW with wire filler was designed. The PSD control arithmetic was analyzed, simulating experiment by MATLAB software was done, and the validating experiments on varied heat sink workpiece and varied gap workpiece were successfully implemented. The study results show that the neuron self-learning PSD control method can attain a perfect control effect under different set values and conditions, and is suitable for the welding process with the varied structure and coefficients of control model.
文摘The weld pool shape control by intelligent strategy was studied. In order to improve the ability of self-learning and self-adaptation of the ordinary fuzzy control, a self-learning fuzzy neural network controller (FNNC) for backside width of weld pool in pulsed gas tungsten arc welding (GTAW) with wire filler was designed. In FNNC, the fuzzy system was expressed by an equivalence neural network, the membership functions and inference rulers were decided through the learning of the neural network. Then, the FNNC control arithmetic was analyzed, simulating experiment was done, and the validating experiments on varied heat sink workpiece and varied gap workpiece were implemented. The maximum error between the real value and the given one was 0.39mm, the mean error was 0.014mm, and the root-mean-square was 0.14mm. The real backside width was maintained around the given value. The results show that the self-learning fuzzy neural network control strategy can achieve a perfect control effect under different set values and conditions, and is suitable for the welding process with the varied structure and coefficients of control model.
基金National Natural Science Foundation of China under Grant 61825305,62003361,U21A20518.
文摘Human-machine cooperative control has become an important area of intelligent driving,where driver intention recognition and dynamic control authority allocation are key factors for improving the performance of cooperative decision-making and control.In this paper,an online learning method is proposed for human-machine cooperative control,which introduces a priority control parameter in the reward function to achieve optimal allocation of control authority under different driver intentions and driving safety conditions.Firstly,a two-layer LSTM-based sequence prediction algorithm is proposed to recognise the driver's lane change(LC)intention for human-machine cooperative steering control.Secondly,an online reinforcement learning method is developed for optimising the steering authority to reduce driver workload and improve driving safety.The driver-in-the-loop simulation results show that our method can accurately predict the driver's LC intention in cooperative driving and effectively compensate for the driver's non-optimal driving actions.The experimental results on a real intelligent vehicle further demonstrate the online optimisation capability of the proposed RL-based control authority allocation algorithm and its effectiveness in improving driving safety.
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
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Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Science Foundation of China(No.62171387)the Science and Technology Program of Sichuan Province(No.2024NSFSC0468)the China Postdoctoral Science Foundation(No.2019M663475).
文摘As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and diverse communication needs.It is crucial to design control sequences with robust randomness and conflict-freeness to properly address differentiated access control in data link.In this paper,we propose a hierarchical access control scheme based on control sequences to achieve high utilization of time slots and differentiated access control.A theoretical bound of the hierarchical control sequence set is derived to characterize the constraints on the parameters of the sequence set.Moreover,two classes of optimal hierarchical control sequence sets satisfying the theoretical bound are constructed,both of which enable the scheme to achieve maximum utilization of time slots.Compared with the fixed time slot allocation scheme,our scheme reduces the symbol error rate by up to 9%,which indicates a significant improvement in anti-interference and eavesdropping capabilities.
文摘In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regional controllability is more adapted to systems described by dynamic systems.Regional controllability results in a strategic area were established for vibrating plates by the Hilbertian Uniqueness Method.
基金supported by Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020261)Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA02010000)the Young Potential Program of Shanghai Institute of Applied Physics,Chinese Academy of Sciences(No.SINAP-YXJH-202412).
文摘Molten salt reactors,being the only reactor type among Generation Ⅳ advanced nuclear reactors that utilize liquid fuels,offer inherent safety,high-temperature,and low-pressure operation,as well as the capability for online fuel reprocessing.However,the fuel-salt flow results in the decay of delayed neutron precursors(DNPs)outside the core,causing fluctuations in the effective delayed neutron fraction and consequently impacting the reactor reactivity.Particularly in accident scenarios—such as a combined pump shutdown and the inability to rapidly scram the reactor—the sole reliance on negative temperature feedback may cause a significant increase in core temperature,posing a threat to reactor safety.To address these problems,this paper introduces an innovative design for a passive fluid-driven suspended control rod(SCR)to dynamically compensate for reactivity fluctuations caused by DNPs flowing with the fuel.The control rod operates passively by leveraging the combined effects of gravity,buoyancy,and fluid dynamic forces,thereby eliminating the need for an external drive mechanism and enabling direct integration within the active region of the core.Using a 150 MWt thorium-based molten salt reactor as the reference design,we develop a mathematical model to systematically analyze the effects of key parameters—including the geometric dimensions and density of the SCR—on its performance.We examine its motion characteristics under different core flow conditions and assess its feasibility for the dynamic compensation of reactivity changes caused by fuel flow.The results of this study demonstrate that the SCR can effectively counteract reactivity fluctuations induced by fuel flow within molten salt reactors.A sensitivity analysis reveals that the SCR’s average density exerts a profound impact on its start-up flow threshold,channel flow rate,resistance to fuel density fluctuations,and response characteristics.This underscores the critical need to optimize this parameter.Moreover,by judiciously selecting the SCR’s length,number of deployed units,and the placement we can achieve the necessary reactivity control while maintaining a favorable balance between neutron economy and heat transfer performance.Ultimately,this paper provides an innovative solution for the passive reactivity control in molten salt reactors,offering significant potential for practical engineering applications.
文摘Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.
基金supported in part by the National Natural Science Foundation of China,Grant/Award Number:62003267the Key Research and Development Program of Shaanxi Province,Grant/Award Number:2023-GHZD-33Open Project of the State Key Laboratory of Intelligent Game,Grant/Award Number:ZBKF-23-05。
文摘To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.
文摘AIM:To investigate the effects of binocular fusional C-optotypes(positive/negative)and 2D planar C-optotypes on the amplitude and stability of transient accommodation(TAC)in adults,and to provide a basis for non-contact myopia intervention.METHODS:This was a self-controlled study.Using redblue 3D technology,four experimental stages were set up:Test A[fixating on the 1 m negative fusional C-optotypes,8△base-in(BI)],Test B(fixating on the 5 m planar C-optotypes),Test C(fixating on the 1 m planar C-optotypes),and Test D[fixating on the 1 m positive fusional C-optotypes,20△base-out(BO)].A WAM-5500 open-field autorefractor was used to measure TAC and accommodative microfluctuations[evaluated via interquartile range(IQR)and median-based coefficient of variation(CVmed)].Additionally,the convergence accommodation to convergence(CA/C)ratio was calculated,and a visual fatigue questionnaire was administered to assess participants’subjective visual comfort.RESULTS:A total of 21 subjects(7 males,14 females;aged 23-41y)with normal binocular visual function were enrolled.The results showed that the TAC increased gradually across the four stages,and these values were Test A(-0.35±0.26 D)<Test B(-0.46±0.24 D)<Test C(-0.77±0.32 D)<Test D(-1.38±0.31 D).There were significant overall differences(F=56.136,P<0.001).Compared with Test C,Test A reduced TAC by 0.42 D(P<0.05),while Test D increased it by 0.61 D(P<0.001).There was no significant intergroup difference in accommodative fluctuation amplitude(all P>0.05),but the fluctuation stability of Test D showed a significant difference between the first 20s and the second 20s(P=0.017).The CA/C ratio was significantly higher in Test D(0.05±0.02 D/△)than in Test A(0.03±0.02 D/△,P=0.007),indicating stronger accommodation-convergence linkage during positive fusional fixation.The visual fatigue scores of all stages were low(median 0-1),with Test D slightly higher than Test B and Test C(P<0.05).No linear correlation was found between TAC and age(all r<0.1,P>0.05).CONCLUSION:Negative fusional C-optotypes induce ciliary muscle relaxation to reduce TAC,while positive fusional C-optotypes enhance accommodation-convergence coordination to increase TAC.The red-blue 3D-based noncontact training mode exhibits good safety(median visual fatigue scores:0-1 across all tests)and provides a novel dual-directional(relaxation-activation)strategy for myopia prevention and control.
基金supported by Guangdong Basic and Applied Basic Research Foundation(Nos.2023A1515110824 and 2025A1515011839)Shenzhen Science and Technology Program(No.RCBS20231211090638066).
文摘Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.
文摘The concept of Damage Control Surgery(DCS)emphasizes prioritizing hemorrhage control,preventing hypothermia,correcting coagulopathy,and acidosis in trauma treatment.The application of the DCS concept in trauma treatment at grassroots hospitals faces numerous challenges such as limited resources,high technical difficulty,and insufficient multidisciplinary collaboration.Therefore,DCS strategies need to be adapted to simplified processes to create conditions for subsequent treatment.This paper retrieves relevant literature to discuss the proposal,promotion,and application of the DCS concept,aiming to provide evidence-based basis for optimizing trauma treatment outcomes at grassroots hospitals.
基金supported by Natural Science Foundation of Shanghai,under the Shanghai Action Plan for Science,Technology and Innovation(22ZR1464800).
文摘Driven by the global energy transition and carbon neutrality targets,alkaline water electrolysis has emerged as a key technology for coupling variable renewable generation with clean hydrogen production,offering considerable potential for absorbing surplus power and enhancing grid flexibility.However,conventional control architectures typically treat the power converter and electrolyzer as independent units,neglecting their dynamic interactions and thereby limiting overall system performance under practical operating conditions.This review critically examines existing control approaches,ranging from classical proportional-integral schemes to model predictive control,fuzzy-logic algorithms,and data-driven methods,evaluating their effectiveness in managing dynamic response,multivariable coupling,and operational constraints as well as their inherent limitations.Attention is then focused on the performance requirements of the hydrogen-production converter,including current ripple suppression,rapid transient response,adaptive thermal regulation,and stable power delivery.An integrated co‑control framework is proposed,aligning converter output with electrolyzer demand across steady-state operation,variable renewable input,and emergency shutdown scenarios to achieve higher efficiency,extended equipment lifetime,and enhanced operational safety.Finally,prospects for advancing unified control methodologies are outlined,with emphasis on constraint-aware predictive control,machine-learning-enhanced modeling,and real‑time co‑optimization for future alkaline electrolyzer systems.
