As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imagi...
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As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.
Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperati...
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Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperative decision-making,it is challenging for existing MARL algorithms to quickly converge to an optimal strategy for UCAV formation in BVR air combat where confrontation is complicated and reward is extremely sparse and *** to solve this problem,this paper proposes an Advantage Highlight Multi-Agent Proximal Policy Optimization(AHMAPPO)***,at every step,the AHMAPPO records the degree to which the best formation exceeds the average of formations in parallel environments and carries out additional advantage sampling according to ***,the sampling result is introduced into the updating process of the actor network to improve its optimization ***,the simulation results reveal that compared with some state-of-the-art MARL algorithms,the AHMAPPO can obtain a more excellent strategy utilizing fewer sample episodes in the UCAV formation BVR air combat simulation environment built in this paper,which can reflect the critical features of BVR air *** AHMAPPO can significantly increase the convergence efficiency of the strategy for UCAV formation in BVR air combat,with a maximum increase of 81.5%relative to other algorithms.
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...
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Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical *** improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation *** the motion of the UAV platform,the echo signal is sampled at different ***,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal *** the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of *** results of numerical simulations conducted herein verify the superior performance of the proposed method.
To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-lea...
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To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is ***,dividing the distance between the missile and the target into multiple states to increase the quantity of state ***,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference *** interference effect is determined by detecting whether the fuze signal ***,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference *** effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile *** optimal interference form for each distance state has been *** with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.
Because of their advantages of high energy and power density,low self-discharge rate,and long lifespan,lithium-ion batteries(LIBs)have been widely used in many applications such as electric vehicles,energy storage sys...
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Because of their advantages of high energy and power density,low self-discharge rate,and long lifespan,lithium-ion batteries(LIBs)have been widely used in many applications such as electric vehicles,energy storage systems,smart grids,***,lithium-ion battery systems(LIBSs)frequently malfunction because of complex working conditions,harsh operating environment,battery inconsistency,and inherent defects in battery ***,safety of LIBSs has become a prominent problem and has attracted wide ***,efficient and accurate fault diagnosis for LIBs is very *** paper provides a comprehensive review of the latest research progress in fault diagnosis for ***,the types of battery faults are comprehensively introduced and the characteristics of each fault are ***,the fault diagnosis methods are systematically elaborated,including model-based,data processing-based,machine learning-based and knowledge-based *** latest research is discussed and existing issues and challenges are presented,while future developments are also *** aim is to promote further researches into efficient and advanced fault diagnosis methods for more reliable and safer LIBs.
Dear Editor,Any fault of a battery system that is not handled timely can cause catastrophic ***,it is significant to diagnose battery faults early and *** to the complex nonlinear features and inconsistency of lithium...
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Dear Editor,Any fault of a battery system that is not handled timely can cause catastrophic ***,it is significant to diagnose battery faults early and *** to the complex nonlinear features and inconsistency of lithium batteries,traditional fault diagnosis methods usually fail to detect battery minor faults in the early stages.
In this paper,the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems.A signed digraph is presented to describe the collaborative and competitive interactions among...
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In this paper,the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems.A signed digraph is presented to describe the collaborative and competitive interactions among *** each agent with lower triangular structure,a time-varying gain compensator is first designed by relative output information of neighboring ***,a distributed controller with dynamic event-triggered mechanism is proposed to drive the bipartite consensus error to *** is worth noting that an internal dynamic variable is introduced in triggering function,which plays an essential role in excluding the Zeno behavior and reducing energy ***,the dynamic event-triggered control protocol is developed for upper triangular multi-agent systems to realize the bipartite consensus without Zeno ***,simulation examples are provided to illustrate the effectiveness of the presented results.
In this paper,an adaptive control strategy is proposed to investigate the issue of uncertain dead-zone input for nonlinear triangular systems with unknown *** considered system has no precise priori knowledge about th...
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In this paper,an adaptive control strategy is proposed to investigate the issue of uncertain dead-zone input for nonlinear triangular systems with unknown *** considered system has no precise priori knowledge about the dead-zone feature and growth rate of ***,a dynamic gain is introduced to deal with the unknown growth rate,and the dead-zone characteristic is processed by the adaptive estimation approach without constructing the dead-zone ***,by virtue of hyperbolic functions and sign functions,a new adaptive state feedback controller is proposed to guarantee the global boundedness of all signals in the closed-loop ***,the uncertain dead-zone input problem for nonlinear upper-triangular systems is solved by the similar control ***,two simulation examples are given to verify the effectiveness of the control scheme.
The biotransformation of food waste(FW)to bioenergy has attracted considerable research attention as a means to address the energy crisis and waste disposal *** this end,a promising technique is two-stage anaerobic di...
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The biotransformation of food waste(FW)to bioenergy has attracted considerable research attention as a means to address the energy crisis and waste disposal *** this end,a promising technique is two-stage anaerobic digestion(TSAD),in which the FW is transformed to biohythane,a gaseous mixture of biomethane and *** review summarises the main characteristics of FW and describes the basic principle of ***,the factors influencing the TSAD performance are identified,and an overview of the research status;economic aspects;and strategies such as pre-treatment,co-digestion,and regulation of microbial consortia to increase the biohythane yield from TSAD is ***,the challenges and future considerations associated with the treatment of FW by TSAD are *** paper can provide valuable reference for the improvement and widespread implementation of TSAD-based FW treatment.
Focusing on the non-concave trajectory constraint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft...
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Focusing on the non-concave trajectory constraint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft rendezvous and docking terminal phase with external disturbance is investigated in this ***,a fixed-time observer based on real-time differentiator is developed to compensate for the external disturbance,whose estimation error can converge to zero after a time independent of the initial ***,a sliding surface ensuring fixed-time convergence is *** sliding surface can guarantee that the vehicle achieves a non-concave trajectory,which is better for avoiding collision and maintaining the visibility of the landing site or docking ***,the nonsingular guidance ensuring the fixed-time convergence of the sliding surface is proposed,which is continuous and chatter *** last,three numerical simulations of Mars landing are performed to validate the effectiveness and correctness of the designed scheme.
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