建立了光伏电池数学模型,研究了其在不同光照模式下的非线性。在此基础上建立了多片光伏板组成的电池阵列模型,研究了其输出功率的多峰值特性。针对传统最大功率点跟踪(Maximum Power Point Tracking, MPPT)算法无法有效跟踪控制多峰值...建立了光伏电池数学模型,研究了其在不同光照模式下的非线性。在此基础上建立了多片光伏板组成的电池阵列模型,研究了其输出功率的多峰值特性。针对传统最大功率点跟踪(Maximum Power Point Tracking, MPPT)算法无法有效跟踪控制多峰值的问题,研究了改进粒子群算法的MPPT,通过粒子群在历史最佳位置和所有粒子中找到全局最优位置。实验结果表明,该算法能够有效解决传统算法无法解决的复杂多峰值问题,并且具有更高的追踪效率和适应性。展开更多
Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and ...Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.展开更多
一类改进的最优转矩(optimal torque, OT)法通过扩大风力机最大功率点跟踪(maximum power point tracking, MPPT)过程中的不平衡转矩来提升转速跟踪能力,进而捕获更多风能。然而,此类方法在提高风能捕获效率的同时会造成电磁转矩的频繁...一类改进的最优转矩(optimal torque, OT)法通过扩大风力机最大功率点跟踪(maximum power point tracking, MPPT)过程中的不平衡转矩来提升转速跟踪能力,进而捕获更多风能。然而,此类方法在提高风能捕获效率的同时会造成电磁转矩的频繁波动,导致风力机传动链载荷显著提升。针对这一问题,文中研究发现在风速变化下补偿转矩引起的额外电磁转矩波动是产生上述现象的主要原因。为此,文中提出一种考虑载荷影响的风力机加速OT法,在风速变化时通过利用恒转矩过渡阶段抑制额外的电磁转矩波动,提升MPPT过程中的转速跟踪能力,从而实现在提升风力机风能捕获效率的同时尽可能避免载荷增大。最后,仿真结果验证表明,文中所提加速OT法不仅可以提升不同风况下的风能捕获效率,而且能够有效抑制传动链载荷的上升。展开更多
局部阴影条件下,光伏阵列的P-U曲线呈多峰状态,常规的最大功率点追踪MPPT(maximum power point tracking)算法容易陷入局部极值,无法及时精确地跟踪光伏发电系统的最大功率点,针对此问题提出1种基于改进蜣螂IDBO(improved dung beetle o...局部阴影条件下,光伏阵列的P-U曲线呈多峰状态,常规的最大功率点追踪MPPT(maximum power point tracking)算法容易陷入局部极值,无法及时精确地跟踪光伏发电系统的最大功率点,针对此问题提出1种基于改进蜣螂IDBO(improved dung beetle optimizer)算法的MPPT控制策略。首先对蜣螂种群的初始化进行针对性优化,并在位置更新过程中引入Levy飞行策略。通过在MATLAB/Simulink平台进行仿真验证及实物实验验证,证明了IDBO算法相较于传统算法,无论是在静态还是动态条件下,均能更快且更稳定地找到全局最大功率点。展开更多
光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽...光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽样初始化种群代替粒子群算法中随机初始化种群,保证初始化的种群更加均匀。同时使用自适应权重代替固定权重,更好地平衡粒子群的探索和开发能力,避免算法过早地陷入局部最优解。在Matlab/Simulink中搭建光伏系统MPPT仿真模型,通过均匀光照、静态遮阴光照和动态遮阴光照3种情况下的仿真对比,所提的改进粒子群优化算法比扰动观察法和粒子群优化算法有更好的追踪精度,验证所提算法在光伏MPPT控制中的有效性。展开更多
针对传统扰动观察法在光伏系统最大功率点跟踪(Maximum Power Point Tracking,MPPT)中存在步长选取不能同时兼顾跟踪速度及稳态精度的问题,在可变工作环境下建立起光伏系统最大功率点电压与环境温度和光照强度之间的数学表达式,获得可...针对传统扰动观察法在光伏系统最大功率点跟踪(Maximum Power Point Tracking,MPPT)中存在步长选取不能同时兼顾跟踪速度及稳态精度的问题,在可变工作环境下建立起光伏系统最大功率点电压与环境温度和光照强度之间的数学表达式,获得可变环境下光伏系统最大功率点电压值,再将其赋值给小步长扰动观察法。仿真分析结果表明,相比恒定电压-扰动观察法,所提方法具有更快跟踪速度和更高稳态精度。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
Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the ...Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the fish’s behavior,health,and environmental adaptability.However,when multi-object tracking(MOT)algorithms are applied to the high-density aquaculture environment,occlusion and overlapping among fish may result in missed detections,false detections,and identity switching problems,which limit the tracking accuracy.To address these issues,this paper proposes FishTracker,a MOT algorithm,by utilizing a Tracking-by-Detection framework.First,the neck part of the YOLOv8 model is enhanced by introducing a Multi-Scale Dilated Attention(MSDA)module to improve object localization and classification confidence.Second,an Adaptive Kalman Filter(AKF)is employed in the tracking phase to dynamically adjust motion prediction parameters,thereby overcoming target adhesion and nonlinear motion in complex scenarios.Experimental results show that FishTracker achieves a multi-object tracking accuracy(MOTA)of 93.22% and 87.24% in bright and dark illumination conditions,respectively.Further validation in a real aquaculture scenario reveal that FishTracker achieves aMOTA of 76.70%,which is 5.34% higher than the baselinemodel.The higher order tracking accuracy(HOTA)reaches 50.5%,which is 3.4% higher than the benchmark.In conclusion,FishTracker can provide reliable technical support for accurate tracking and behavioral analysis of high-density fish populations.展开更多
The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is...The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.展开更多
This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aeria...This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aerial vehicle(UAV) targets in low-altitude airspace.A novel UAV visual tracking method is proposed for dynamic structural distortions,with a focus on structural consistency modeling to improve system robustness in complex scenarios.Unlike prior methods such as STARK,which rely on spatio-temporal prediction,and KeepTrack,which emphasize template maintenance,our approach enforces structural-level consistency between historical and current features,thereby addressing UAV-specific issues of rapid maneuvering and environmental complexity.The proposed framework features a structure-aware architecture that incorporates dual complementary mechanisms serving as spatial completion and temporal restoration components.First,a multi-scale structure extraction module with adaptive anchor scheduling is developed to dynamically perceive spatial target shape and generate high-quality proposals.Second,a structural memory module is designed to reconstruct local regions by leveraging high-confidence historical structural representations,thereby maintaining spatiotemporal coherence across frames.Furthermore,a structural verification mechanism coupled with a meta-learning-driven re-identification strategy is introduced to detect abrupt structural distortions and adaptively update templates,significantly improving resilience against disturbances.Overall,the main contributions of this paper can be summarized as follows:(1) introducing structural consistency modeling into UAV visual tracking for the first time;(2) designing a unified framework that combines adaptive proposal generation,full-image matching,and re-identification under structural constraints;and(3) achieving state-of-the-art performance on the anti-UAV benchmark,highlighting the method's practical value in real-world UAV surveillance applications.展开更多
This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity p...This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.展开更多
为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power...为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power Point Tracking,MPPT)电路架构。对压电源的阻抗特性进行分析,采用了基于快速开关电容采样的开路电压采样MPPT算法,有效实现跟踪精度和动态响应速度的协同优化。最后,基于0.18μm BCD工艺对电路进行设计,仿真结果表明:MPPT的跟踪时间为0.36 ms,最大追踪精度可达99.4%。展开更多
文摘建立了光伏电池数学模型,研究了其在不同光照模式下的非线性。在此基础上建立了多片光伏板组成的电池阵列模型,研究了其输出功率的多峰值特性。针对传统最大功率点跟踪(Maximum Power Point Tracking, MPPT)算法无法有效跟踪控制多峰值的问题,研究了改进粒子群算法的MPPT,通过粒子群在历史最佳位置和所有粒子中找到全局最优位置。实验结果表明,该算法能够有效解决传统算法无法解决的复杂多峰值问题,并且具有更高的追踪效率和适应性。
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project(Grant No.RGP2/587/46).
文摘Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.
文摘一类改进的最优转矩(optimal torque, OT)法通过扩大风力机最大功率点跟踪(maximum power point tracking, MPPT)过程中的不平衡转矩来提升转速跟踪能力,进而捕获更多风能。然而,此类方法在提高风能捕获效率的同时会造成电磁转矩的频繁波动,导致风力机传动链载荷显著提升。针对这一问题,文中研究发现在风速变化下补偿转矩引起的额外电磁转矩波动是产生上述现象的主要原因。为此,文中提出一种考虑载荷影响的风力机加速OT法,在风速变化时通过利用恒转矩过渡阶段抑制额外的电磁转矩波动,提升MPPT过程中的转速跟踪能力,从而实现在提升风力机风能捕获效率的同时尽可能避免载荷增大。最后,仿真结果验证表明,文中所提加速OT法不仅可以提升不同风况下的风能捕获效率,而且能够有效抑制传动链载荷的上升。
文摘局部阴影条件下,光伏阵列的P-U曲线呈多峰状态,常规的最大功率点追踪MPPT(maximum power point tracking)算法容易陷入局部极值,无法及时精确地跟踪光伏发电系统的最大功率点,针对此问题提出1种基于改进蜣螂IDBO(improved dung beetle optimizer)算法的MPPT控制策略。首先对蜣螂种群的初始化进行针对性优化,并在位置更新过程中引入Levy飞行策略。通过在MATLAB/Simulink平台进行仿真验证及实物实验验证,证明了IDBO算法相较于传统算法,无论是在静态还是动态条件下,均能更快且更稳定地找到全局最大功率点。
文摘光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽样初始化种群代替粒子群算法中随机初始化种群,保证初始化的种群更加均匀。同时使用自适应权重代替固定权重,更好地平衡粒子群的探索和开发能力,避免算法过早地陷入局部最优解。在Matlab/Simulink中搭建光伏系统MPPT仿真模型,通过均匀光照、静态遮阴光照和动态遮阴光照3种情况下的仿真对比,所提的改进粒子群优化算法比扰动观察法和粒子群优化算法有更好的追踪精度,验证所提算法在光伏MPPT控制中的有效性。
文摘针对传统扰动观察法在光伏系统最大功率点跟踪(Maximum Power Point Tracking,MPPT)中存在步长选取不能同时兼顾跟踪速度及稳态精度的问题,在可变工作环境下建立起光伏系统最大功率点电压与环境温度和光照强度之间的数学表达式,获得可变环境下光伏系统最大功率点电压值,再将其赋值给小步长扰动观察法。仿真分析结果表明,相比恒定电压-扰动观察法,所提方法具有更快跟踪速度和更高稳态精度。
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.
基金funded by the Fundamental Research Funds for the Central Universities(Grant No.106-YDZX2025022)the Startup Foundation of New Professor at Nanjing Agricultural University(Grant No.106-804005)the“Qing Lan Project”of Jiangsu Higher Education Institutions.
文摘Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the fish’s behavior,health,and environmental adaptability.However,when multi-object tracking(MOT)algorithms are applied to the high-density aquaculture environment,occlusion and overlapping among fish may result in missed detections,false detections,and identity switching problems,which limit the tracking accuracy.To address these issues,this paper proposes FishTracker,a MOT algorithm,by utilizing a Tracking-by-Detection framework.First,the neck part of the YOLOv8 model is enhanced by introducing a Multi-Scale Dilated Attention(MSDA)module to improve object localization and classification confidence.Second,an Adaptive Kalman Filter(AKF)is employed in the tracking phase to dynamically adjust motion prediction parameters,thereby overcoming target adhesion and nonlinear motion in complex scenarios.Experimental results show that FishTracker achieves a multi-object tracking accuracy(MOTA)of 93.22% and 87.24% in bright and dark illumination conditions,respectively.Further validation in a real aquaculture scenario reveal that FishTracker achieves aMOTA of 76.70%,which is 5.34% higher than the baselinemodel.The higher order tracking accuracy(HOTA)reaches 50.5%,which is 3.4% higher than the benchmark.In conclusion,FishTracker can provide reliable technical support for accurate tracking and behavioral analysis of high-density fish populations.
基金part supported by the National Natural Science Foundation(62203034,62273126,62203035)the Ling-Yan Research and Development Project of Zhejiang Province of China(2023C03185)。
文摘The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.
基金Supported by the National Science Foundation of China (No.62571164)the Natural Science Foundation of Heilongjiang Province (No.PL2024F025)the Fundamental Scientific Research Funds of Heilongjiang Province (No.2022-KYYWF-1050)。
文摘This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aerial vehicle(UAV) targets in low-altitude airspace.A novel UAV visual tracking method is proposed for dynamic structural distortions,with a focus on structural consistency modeling to improve system robustness in complex scenarios.Unlike prior methods such as STARK,which rely on spatio-temporal prediction,and KeepTrack,which emphasize template maintenance,our approach enforces structural-level consistency between historical and current features,thereby addressing UAV-specific issues of rapid maneuvering and environmental complexity.The proposed framework features a structure-aware architecture that incorporates dual complementary mechanisms serving as spatial completion and temporal restoration components.First,a multi-scale structure extraction module with adaptive anchor scheduling is developed to dynamically perceive spatial target shape and generate high-quality proposals.Second,a structural memory module is designed to reconstruct local regions by leveraging high-confidence historical structural representations,thereby maintaining spatiotemporal coherence across frames.Furthermore,a structural verification mechanism coupled with a meta-learning-driven re-identification strategy is introduced to detect abrupt structural distortions and adaptively update templates,significantly improving resilience against disturbances.Overall,the main contributions of this paper can be summarized as follows:(1) introducing structural consistency modeling into UAV visual tracking for the first time;(2) designing a unified framework that combines adaptive proposal generation,full-image matching,and re-identification under structural constraints;and(3) achieving state-of-the-art performance on the anti-UAV benchmark,highlighting the method's practical value in real-world UAV surveillance applications.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China (No.LR23F030002)。
文摘This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.
文摘为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power Point Tracking,MPPT)电路架构。对压电源的阻抗特性进行分析,采用了基于快速开关电容采样的开路电压采样MPPT算法,有效实现跟踪精度和动态响应速度的协同优化。最后,基于0.18μm BCD工艺对电路进行设计,仿真结果表明:MPPT的跟踪时间为0.36 ms,最大追踪精度可达99.4%。
