期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到16,738篇文章
< 1 2 … 250 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Optimization of a self-tuning force control system for the milling process using a dynamic enhanced genetic algorithm 认领 引用
1
作者 Yao Li Zhengcai Zhao +3 位作者 Ning Qian Lei Zhang Wenfeng Ding Yucan Fu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第2期33-43,共11页
When milling structural components with varying axial depths and widths,cutting forces tend to fluctuate,negatively impacting tool life and machining accuracy.To mitigate the force fluctuations and enhance tool longev... When milling structural components with varying axial depths and widths,cutting forces tend to fluctuate,negatively impacting tool life and machining accuracy.To mitigate the force fluctuations and enhance tool longevity,developing a simple,reliable,and easy-to-implement force control system for milling is essential,which is an important step toward advancing intelligent manufacturing.This paper explores the use of genetic algorithms(GA) for powerful optimization capabilities in developing self-tuning milling force controllers.A comprehensive framework for optimizing a fuzzy logic controller using an enhanced GA is specifically designed for the milling process.The optimization integrates the GA with a simulation model,fine-tuning membership functions and optimizing fuzzy rule selection.The enhanced GA incorporates the Integral of Time-weighted Absolute Error(ITAE) as the fitness criterion to improve the robustness and responsiveness of the controller.The optimized fuzzy logic controller is implemented within a computer numerical control system,adjusting feed rates in real-time to control milling forces.The performance of the proposed controller is validated through step and slope milling tests,demonstrating an average control accuracy of 95.52%.Comparative evaluations with other controllers show that the proposed system offers a significant improvement,achieving up to 4.58% better control accuracy in step milling tests. 展开更多
关键词 Optimization Self-tuning Force control system Milling process Genetic algorithm
暂未订购 下载PDF
Data-Driven Algorithms for Finite-Horizon and Infinite-Horizon Indefinite Linear Quadratic Stochastic Optimal Control Problems 认领 引用
2
作者 Guangchen Wang Heng Zhang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1459-1469,共11页
This paper is devoted to devising data-driven algorithms for finite-horizon and infinite-horizon linear quadratic stochastic optimal control(LQSOC)problems.In our study,the diffusion terms of system dynamics are permi... This paper is devoted to devising data-driven algorithms for finite-horizon and infinite-horizon linear quadratic stochastic optimal control(LQSOC)problems.In our study,the diffusion terms of system dynamics are permitted to hinge upon both control and state variables,and the weighting matrices of cost functionals are allowed to be indefinite.It is acknowledged that the optimal controls of finite-horizon and infinite-horizon indefinite LQSOC problems are correlated with a generalized differential Riccati equation(GDRE)and a generalized algebraic Riccati equation(GARE).Herein,we propose two data-driven algorithms to approximate the solutions of these Riccati equations,and thereby determine optimal controls,without leveraging the information of all system parameters.Additionally,we prove the convergence of these algorithms and examine the impact of computational errors.Finally,we validate the performance of these data-driven algorithms via three simulation examples. 展开更多
关键词 Data-driven algorithm generalized algebraic Riccati equation (GARE) generalized differential Riccati equation (GDRE) indefinite problem linear quadratic stochastic optimal control (LQSOC)
暂未订购 下载PDF
PID Steering Control Method of Agricultural Robot Based on Fusion of Particle Swarm Optimization and Genetic Algorithm 认领 引用 被引量：2
3
作者 ZHAO Longlian ZHANG Jiachuang +2 位作者 LI Mei DONG Zhicheng LI Junhui 《农业机械学报》 EI CAS CSCD 北大核心 2026年第1期358-367,共10页
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
关键词 agricultural robot steering PID control particle swarm optimization algorithm genetic algorithm
暂未订购 下载PDF
Temperature control for liquid-cooled fuel cells based on fuzzy logic and variable-gain generalized supertwisting algorithm 认领 引用
4
作者 CHEN Lin JIA Zhi-huan +1 位作者 DING Tian-wei GAO Jin-wu 《控制理论与应用》 EI CAS CSCD 北大核心 2025年第8期1596-1605,共10页
The liquid cooling system(LCS)of fuel cells is challenged by significant time delays,model uncertainties,pump and fan coupling,and frequent disturbances,leading to overshoot and control oscillations that degrade tempe... The liquid cooling system(LCS)of fuel cells is challenged by significant time delays,model uncertainties,pump and fan coupling,and frequent disturbances,leading to overshoot and control oscillations that degrade temperature regulation performance.To address these challenges,we propose a composite control scheme combining fuzzy logic and a variable-gain generalized supertwisting algorithm(VG-GSTA).Firstly,a one-dimensional(1D)fuzzy logic controler(FLC)for the pump ensures stable coolant flow,while a two-dimensional(2D)FLC for the fan regulates the stack temperature near the reference value.The VG-GSTA is then introduced to eliminate steady-state errors,offering resistance to disturbances and minimizing control oscillations.The equilibrium optimizer is used to fine-tune VG-GSTA parameters.Co-simulation verifies the effectiveness of our method,demonstrating its advantages in terms of disturbance immunity,overshoot suppression,tracking accuracy and response speed. 展开更多
关键词 liquid-cooled fuel cell temperature control generalized supertwisting algorithm fuzzy control equilibrium optimizer
暂未订购 下载PDF
Optimal load frequency control system for two-area connected via AC/DC link using cuckoo search algorithm 认领 引用
5
作者 Gaber EL-SAADY Alexey MIKHAYLOV +2 位作者 Nora BARANYAI Mahrous AHMED Mahmoud HEMEIDA 《虚拟现实与智能硬件（中英文）》 EI CSCD 2025年第3期299-316,共18页
Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a ... Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a two-area power system.Methods Two areas were connected through an AC tie line in parallel with a DC link to stabilize the frequency of oscillations in both areas.The PI parameters were tuned using the cuckoo search algorithm(CSA)to minimize the integral absolute error(IAE).A state matrix was provided,and the stability of the system was verified by calculating the eigenvalues.The frequency response was investigated for load variation,changes in the generator rate constraint,the turbine time constant,and the governor time constant.Results The CSA was compared with particle swarm optimization algorithm(PSO)under identical conditions.The system was modeled based on a state-space mathematical representation and simulated using MATLAB.The results demonstrated the effectiveness of the proposed controller based on both algorithms and,it is clear that CSA is superior to PSO.Conclusion The CSA algorithm smoothens the system response,reduces ripples,decreases overshooting and settling time,and improves the overall system performance under different disturbances. 展开更多
关键词 Load frequency control Cuckoo search algorithm PI controllers State space modeling
暂未订购 下载PDF
A new fixed-depth suspension control algorithm for mobile marine seismometer and its testing results 认领 引用
6
作者 Fei Hou Jiabiao Li +2 位作者 Xinke Zhu Weiwei Ding Zhiteng Yu 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2025年第2期91-103,共13页
A mobile marine seismometer(MMS)is a vertical underwater vehicle that detects ocean seismic waves.One of the critical operational requirements for an MMS is that it remains suspended at a desired depth.This article ai... A mobile marine seismometer(MMS)is a vertical underwater vehicle that detects ocean seismic waves.One of the critical operational requirements for an MMS is that it remains suspended at a desired depth.This article aimed to propose a fixed-depth suspension control for the MMS with a limited onboard energy supply.The research team established a kinematic model to analyze fluctuations in the vertical motion of the MMS and the delayed response of the system.We ascertained a direct one-to-one correlation between the displacement volume of the mobile ocean seismic instrument and the depth at which it reaches a state of neutral buoyancy(commonly referred to as the hover depth).A fixed-depth control algorithm was introduced,allowing a gradual approach to the necessary displacement volume to reach the desired suspension depth.The study optimized the boundary conditions to reduce unnecessary adjustments and mitigate the time delay caused by the instrument’s inertia,thereby significantly minimizing energy consumption.This method does not require calculating the hydrodynamic parameters or transfer functions of the MMS,thereby considerably reducing the implementation complexity.In the three-month sea trial in the South China Sea,the seismic instrument was set to hover at 800 m,with a permissible fluctuation of±100 m,operating on a seven-day cycle.The experimental results show that the seismic instrument has an average hover error of 34.6 m,with a vertical drift depth of 29.6 m per cycle,and the buoyancy adjustment system made six adjustments,indicating that our proposed control method performs satisfactorily.In addition,this method provides new insights for the fixed-depth control of other ocean observation devices that rely on buoyancy adjustment. 展开更多
关键词 mobile marine seismometer fixed-depth control algorithm low buoyancy-adjustment cost faster convergence speed
暂未订购 下载PDF
Fishing Ship Trajectory Tracking Control Based on the Closed-Loop Gain Shaping Algorithm Under Rough Sea 认领 引用
7
作者 SONG Chun-yu GUO Te-er SUI Jiang-hua 《China Ocean Engineering》 SCIE EI CSCD 2025年第2期365-372,共8页
This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working... This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships. 展开更多
关键词 trajectory tracking control nonlinear feedback control fishing ship closed-loop gain shaping algorithm rough sea
暂未订购 下载PDF
Parametric control of UAV U-turns in turbulent wind conditions based on global optimization 认领 引用
8
作者 Liguo TAN Yongcheng XIONG +3 位作者 Changqing HU Jianfeng LI Oleg KUZENKOV Samvel NALCHAJYAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期398-409,共12页
Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a nove... Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions.First,the equations of motion for the aircraft are reformulated as a system of stochastic differential equations,which are subsequently transformed into a deterministic form.By modeling turbulence as a Gaussian random process and incorporating it directly into the control system,the proposed method proactively compensates for the adverse effects of turbulence.The transformation is achieved using semi-invariant techniques.Second,the control problem is formulated as an optimization task,aiming to minimize the deviation between the actual and desired turn characteristics,specifically the angular velocity.Finally,a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters.Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches,ensuring both stability and precision in turbulent wind conditions. 展开更多
关键词 Parametric control Rigid-wing unmanned aerial vehicle Stochastic system Global optimization Evolutionary algorithm
暂未订购 下载PDF
A Hybrid MZOA-PSO Optimized Cascaded PI(1+DD)-PI-PID Controller for Frequency Stability of Interconnected Power Systems with Renewable Energy and Electric Vehicles 认领 引用
9
作者 AL-Wesabi Ibrahim Hassan M.Hussein Farh +3 位作者 Jiazhu Xu Mohamad A.Alawad Ahmed Alqurashi Abdullrahman A.Al-Shamma’a 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第7期650-697,共48页
Load frequency control(LFC)in interconnected power systems has always been a challenging task in the presence of uncertainty and variability in the power systems arising primarily due to the integration of renewable e... Load frequency control(LFC)in interconnected power systems has always been a challenging task in the presence of uncertainty and variability in the power systems arising primarily due to the integration of renewable energy sources and the impact of electric vehicles on the power system.Although various PI/PID and other advanced control strategies have been employed for LFC in power systems,the existing methods have shown some limitations in terms of dynamic flexibility and robustness in the presence of nonlinearities and couplings in the power systems.Moreover,the optimization methods employed for the tuning of the controllers have shown some limitations in terms of the balance between global and local search abilities of the optimization functions.To overcome the limitations of the existing methods and optimization functions,a hybrid Modified Zebra Optimization Algorithm-Particle Swarm Optimization(MZOA-PSO)is presented in this paper for the optimization of a cascaded PI(1+DD)-PI-PID controller for LFC in power systems.The MZOA enhances the original ZOA by chaotic initialization,adaptive parameter control,and Lévy-flight foraging to improve the global search ability,while PSO ensures efficient local search ability.The optimizer is first validated using four benchmark functions,achieving the global optimum for the Booth and Zakharov functions,a mean value of 2.13×10−28 with a 98%success rate for Rosenbrock,and 3.21×10−81 for Schwefel 2.22.Under a 1%step load perturbation,the proposed controller achieves a 13 s settling time,zero negative deviation in Area 2,a maximum positive excursion of 0.10 Hz,and tie-line undershoot limited to−0.10 p.u.Under random load variations,deviations remain within±0.03 Hz and±0.02 p.u.Under RES and EV integration,the peak frequency deviation is reduced to 0.46 Hz in Area 1.These results confirm that the proposed hybrid MZOA-PSO tuned cascaded controller provides improved damping,faster stabilization,and stronger robustness for modern interconnected LFC systems. 展开更多
关键词 Load frequency control cascaded PI(1+DD)-PI-PID controller hybrid MZOA-PSO algorithm interconnected power systems performance optimization
暂未订购 下载PDF
Actor–Critic Trajectory Controller with Optimal Design for Nonlinear Robotic Systems 认领 引用
10
作者 Nien-Tsu Hu Hsiang-Tung Kao +1 位作者 Chin-Sheng Chen Shih-Hao Chang 《Computers, Materials & Continua》 SCIE EI 2026年第4期1996-2021,共26页
Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are o... Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility. 展开更多
关键词 Reinforcement learning optimal control actor–critic algorithm trajectory tracking nonlinear systems robotic manipulator
暂未订购 下载PDF
Three-degree-of-freedom motion posture stabilization control of platform based on DTW-LSTM-MATD3 under high and low frequency disturbances of ships 认领 引用
11
作者 Qin ZHANG Jingyi ZHOU +1 位作者 Bangping GU Xiong HU 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第3期246-261,共16页
In the complex and variable deep-sea environment,the compensation control of ship motion ensures the safety and efficiency of equipment installation and transportation in offshore wind farms.However,the ship motion po... In the complex and variable deep-sea environment,the compensation control of ship motion ensures the safety and efficiency of equipment installation and transportation in offshore wind farms.However,the ship motion posture compensation control system is severely affected by uncertainties,which significantly impact the accuracy of compensation control.In this paper,we propose a ship three-degree-of-freedom(3-DoF)motion posture stabilization control method based on the DTW-LSTM-MATD3 algorithm.We use the multi-agent twin delayed deep deterministic policy gradient(MATD3)to control a platform with six electric cylinders to achieve stable control.However,owing to random noise affecting the ship’s motion posture,we use a dynamic time warping(DTW)algorithm to distinguish between high-frequency noise and low-frequency tracking signals.Further,we embed a long short-term memory(LSTM)network into the MATD3 network to better align the Critic network’s training with the true Q-value.We use a combined reward function to enhance the agent’s exploration capability in complex dynamic environments.Finally,verification was conducted under sixth-level,abrupt sea conditions with high-frequency noise,as well as under real abrupt sea conditions,and a generalization test was also carried out.Simulation results show that the proposed DTW-LSTM-MATD3 method has great compensation control ability. 展开更多
关键词 Compensation control Multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm Dynamic time warping(DTW)algorithm Long short-term memory(LSTM)network
暂未订购 下载PDF
Improved Whale Optimization-Based Neural Network Predictive Control for Industrial Refrigeration Systems 认领 引用
12
作者 Qi Li Menghan Yang +1 位作者 Shifa Cui Kun Han 《Journal of Harbin Institute of Technology(New Series)》 CAS 2026年第3期1-14,共14页
The inherent nonlinearity and time-delay characteristics of industrial refrigeration processes complicate parameter tuning for conventional PID control,adversely affecting its precision.This makes the control of such ... The inherent nonlinearity and time-delay characteristics of industrial refrigeration processes complicate parameter tuning for conventional PID control,adversely affecting its precision.This makes the control of such systems a significant and challenging research problem.To address this,a novel Neural Network Predictive Control(NNPC)algorithm is proposed,which integrates an Improved Deep Belief Network(IDBN)with an Improved Whale Optimization Algorithm(IWOA).First,the IDBN acts as a high-precision nonlinear prediction model,significantly improving multi-step prediction accuracy.Second,the IWOA is employed to optimize the predictive controller,featuring three major improvements:an improved population initialization,a modified convergence factor update mechanism,and an added disturbance strategy,which collectively accelerate convergence and enhance global search capability.Finally,simulation results demonstrate that the proposed NNPC algorithm achieves superior set-point tracking performance and strong robustness against external disturbances. 展开更多
关键词 industrial refrigeration systems model predictive control time⁃delay whale optimization algorithm deep belief network
暂未订购 下载PDF
Optimized control of grid-connected photovoltaic systems:Robust PI controller based on sparrow search algorithm for smart microgrid application 认领 引用
13
作者 Youssef Akarne Ahmed Essadki +2 位作者 Tamou Nasser Maha Annoukoubi Ssadik Charadi 《Global Energy Interconnection》 EI CSCD 2025年第4期523-536,共14页
The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality,stability,and dynamic environmental variations.Thi... The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality,stability,and dynamic environmental variations.This paper presents a novel sparrow search algorithm(SSA)-tuned proportional-integral(PI)controller for grid-connected photovoltaic(PV)systems,designed to optimize dynamic perfor-mance,energy extraction,and power quality.Key contributions include the development of a systematic SSA-based optimization frame-work for real-time PI parameter tuning,ensuring precise voltage and current regulation,improved maximum power point tracking(MPPT)efficiency,and minimized total harmonic distortion(THD).The proposed approach is evaluated against conventional PSO-based and P&O controllers through comprehensive simulations,demonstrating its superior performance across key metrics:a 39.47%faster response time compared to PSO,a 12.06%increase in peak active power relative to P&O,and a 52.38%reduction in THD,ensuring compliance with IEEE grid standards.Moreover,the SSA-tuned PI controller exhibits enhanced adaptability to dynamic irradiancefluc-tuations,rapid response time,and robust grid integration under varying conditions,making it highly suitable for real-time smart grid applications.This work establishes the SSA-tuned PI controller as a reliable and efficient solution for improving PV system performance in grid-connected scenarios,while also setting the foundation for future research into multi-objective optimization,experimental valida-tion,and hybrid renewable energy systems. 展开更多
关键词 Smart microgrid Photovoltaic system PI controller Sparrow search algorithm Grid-connected Metaheuristic optimization
暂未订购 下载PDF
An Improved Chicken Swarm Optimization Techniques Based on Cultural Algorithm Operators for Biometric Access Control 认领 引用
14
作者 Jonathan Ponmile Oguntoye Sunday Adeola Ajagbe +4 位作者 Oluyinka Titilayo Adedeji Olufemi Olayanju Awodoye Abigail Bola Adetunji Elijah Olusayo Omidiora Matthew Olusegun Adigun 《Computers, Materials & Continua》 SCIE EI 2025年第9期5713-5732,共20页
This study proposes a system for biometric access control utilising the improved Cultural Chicken Swarm Optimization(CCSO)technique.This approach mitigates the limitations of conventional Chicken Swarm Optimization(CS... This study proposes a system for biometric access control utilising the improved Cultural Chicken Swarm Optimization(CCSO)technique.This approach mitigates the limitations of conventional Chicken Swarm Optimization(CSO),especially in dealing with larger dimensions due to diversity loss during solution space exploration.Our experimentation involved 600 sample images encompassing facial,iris,and fingerprint data,collected from 200 students at Ladoke Akintola University of Technology(LAUTECH),Ogbomoso.The results demonstrate the remarkable effectiveness of CCSO,yielding accuracy rates of 90.42%,91.67%,and 91.25%within 54.77,27.35,and 113.92 s for facial,fingerprint,and iris biometrics,respectively.These outcomes significantly outperform those achieved by the conventional CSO technique,which produced accuracy rates of 82.92%,86.25%,and 84.58%at 92.57,63.96,and 163.94 s for the same biometric modalities.The study’s findings reveal that CCSO,through its integration of Cultural Algorithm(CA)Operators into CSO,not only enhances algorithm performance,exhibiting computational efficiency and superior accuracy,but also carries broader implications beyond biometric systems.This innovation offers practical benefits in terms of security enhancement,operational efficiency,and adaptability across diverse user populations,shaping more effective and resource-efficient access control systems with real-world applicability. 展开更多
关键词 Access control biometric technology chicken swarm optimization cultural algorithm pattern recognition
暂未订购 下载PDF
Grid-Connected/Islanded Switching Control Strategy for Photovoltaic Storage Hybrid Inverters Based on Modified Chimpanzee Optimization Algorithm 认领 引用
15
作者 Chao Zhou Narisu Wang +1 位作者 Fuyin Ni Wenchao Zhang 《Energy Engineering》 EI 2025年第1期265-284,共20页
Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,th... Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability. 展开更多
关键词 Photovoltaic storage hybrid inverters modified chimpanzee optimization algorithm droop control seamless switching
暂未订购 下载PDF
A Novel Cascaded TID-FOI Controller Tuned with Walrus Optimization Algorithm for Frequency Regulation of Deregulated Power System 认领 引用
16
作者 Geetanjali Dei Deepak Kumar Gupta +3 位作者 Binod Kumar Sahu Amitkumar V.Jha Bhargav Appasani Nicu Bizon 《Energy Engineering》 EI 2025年第8期3399-3431,共33页
This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation techno... This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation technologies:Area 1 combines thermal,hydro,and distributed generation;Area 2 utilizes a blend of thermal units,distributed solar technologies(DST),and hydro power;andThird control area hosts geothermal power station alongside thermal power generation unit and hydropower units.The suggested control system employs a multi-layered approach,featuring a blended methodology utilizing the Tilted Integral Derivative controller(TID)and the Fractional-Order Integral method to enhance performance and stability.The parameters of this hybrid TID-FOI controller are finely tuned using an advanced optimization method known as the Walrus Optimization Algorithm(WaOA).Performance analysis reveals that the combined TID-FOI controller significantly outperforms the TID and PID controllers when comparing their dynamic response across various system configurations.The study also incorporates investigation of redox flow batteries within the broader scope of energy storage applications to assess their impact on system performance.In addition,the research explores the controller’s effectiveness under different power exchange scenarios in a deregulated market,accounting for restrictions on generation ramp rates and governor hysteresis effects in dynamic control.To ensure the reliability and resilience of the presented methodology,the system transitions and develops across a broad range of varying parameters and stochastic load fluctuation.To wrap up,the study offers a pioneering control approach-a hybrid TID-FOI controller optimized via the Walrus Optimization Algorithm(WaOA)-designed for enhanced stability and performance in a complex,three-region hybrid energy system functioning within a deregulated framework. 展开更多
关键词 Integral time multiplied by absolute error(ITAE) load frequency control(LFC) particle swarm optimization(PSO) tilted integral derivative controller(TID) independent system operator(ISO) walrus optimization algorithm(WaOA) proportional integral derivative controller(PID)
暂未订购 下载PDF
Dynamic Resource Allocation Optimisation and Security-Resilient Control for Bandwidth-Limited Network Control Systems With Data Conflicts 认领 引用
17
作者 Da Chen Kaibo Shi +3 位作者 Bin Guo Kangkang Sun Huaicheng Yan Xiao Cai 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2026年第3期920-934,共15页
Networked control systems(NCSs)often suffer from performance degradation due to limited communication bandwidth,which can cause data transmission conflicts and packet loss.Existing scheduling strategies may fail to si... Networked control systems(NCSs)often suffer from performance degradation due to limited communication bandwidth,which can cause data transmission conflicts and packet loss.Existing scheduling strategies may fail to simultaneously meet the realtime requirements and the importance of multisensor data,and they are particularly vulnerable under distributed denial of service(DDoS)attacks.Firstly,to address these challenges,a greedy algorithm is proposed to optimise the data transmission process to satisfy the importance and real-time requirement of sensor data.It enables the dynamic allocation of network resources,reduces the possibility of data conflict and improves the communication efficiency.Then,an observer-based control algorithm is designed to ensure the system's stability and security resilience under bandwidth constraints and DDoS attacks.Therefore,in the face of packet loss caused by data conflict,the control algorithm can maintain efficient resource scheduling capability and improve the robustness of the system.Finally,the simulation results show that the proposed dynamic resource scheduling framework can guarantee the performance of NCSs under constrained network conditions. 展开更多
关键词 cybersecurity greedy algorithm lyapunov theory network control systems observer‐based control
暂未订购 下载PDF
Driving manipulation analysis and control reconfiguration of heavy-haul trains 认领 引用
18
作者 LI Zi-yi ZHOU Yan-li +2 位作者 YANG Hui YU Yong-sheng LI Guang-wei 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第1期506-522,共17页
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ... The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains. 展开更多
关键词 heavy-haul trains driving manipulation K-means clustering algorithm hidden Markov model control reconfiguration
暂未订购 下载PDF
Novel algorithm of traffic signals adaptive control on urban roads intersections 认领 引用 被引量：1
19
作者 Huanjiong Zhang 《Journal of Highway and Transportation Research and Development(English Edition)》 2025年第1期25-28,共4页
The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability inc... The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability increase,but also the traffic accidents evidently decrease.In this paper,an adaptive algorithm of traffic control signals on the urban roads intersections is designed in,this new algorithm can actively adjust the concrete control times of the traffic control signals based on the perceiving information of the waiting vehicles in real time,then the dynamic balance between the traffic control signals and the traffic flows can be realized.Furthermore,through experiment testing and demonstrating,this adaptive algorithm expresses some fine performances,it also shows good application prospect in the field of smart city. 展开更多
关键词 Traffic engineering Urban road intersections Traffic control signals Perception devices Adaptive algorithm Control phases
暂未订购 下载PDF
An online value iteration method for stochastic linear quadratic control with multiplicative noise 认领 引用
20
作者 Shumei Li Bing-Chang Wang Baoqiang Zhang 《Control Theory and Technology》 EI CSCD 2026年第3期451-461,共11页
This paper proposes a model-free online value iteration(VI)algorithm for solving stochastic linear quadratic control problems with ergodic cost functions,where the diffusion term in the dynamics equation is influenced... This paper proposes a model-free online value iteration(VI)algorithm for solving stochastic linear quadratic control problems with ergodic cost functions,where the diffusion term in the dynamics equation is influenced by both the state and control variables.First,we propose an offline VI algorithm based on the idea of stochastic approximation.However,this algorithm requires prior knowledge of the system parameters,which are not always readily available.To overcome this limitation,we then develop a(partially)model-free online learning algorithm based on VI.This algorithm only requires a single system trajectory and does not need the initial control to be stabilizing.By exploiting the growth rate of Itô’s integrals to handle the stochastic term generated by multiplicative noise,we provide a rigorous proof of the algorithm’s convergence.Finally,a simulation example is presented to validate the convergence of the proposed algorithms. 展开更多
关键词 Stochastic linear quadratic problem Model-free Value iteration algorithm Ergodic control Robust dynamic programming
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈