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Adaptive Data-Driven Coordinated Control of UUVs for Maritime Search and Rescue
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作者 Hao-Liang Wang De-Zhi Yu +1 位作者 Li-Yu Lu Zhou-Hua Peng 《IEEE/CAA Journal of Automatica Sinica》 2025年第9期1953-1955,共3页
Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of... Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of each UUV is totally unknown.Firstly,a kinematic control law is constructed by designing a vertical line-of-sight(LOS)guidance scheme. 展开更多
关键词 data driven control coordinated path following control method coordinated control kinetic model parameters adaptive control unmanned underwater vehicles maritime search rescue unmanned underwater vehicles uuvs
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Data-driven model-free adaptive attitude control of partially constrained combined spacecraft with external disturbances and input saturation 被引量:6
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作者 Han GAO Guangfu MA +1 位作者 Yueyong LYU Yanning GUO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2019年第5期1281-1293,共13页
This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a... This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown. 展开更多
关键词 Attitude control COMBINED SPACECRAFT data-driven control Discrete Extended State Observer(DESO) Input SATURATION
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Data Driven Vibration Control:A Review 被引量:2
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作者 Weiyi Yang Shuai Li Xin Luo 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第9期1898-1917,共20页
With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests... With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic communities.Input shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC methods.It convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration separately.Based on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of DDVC.By doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue. 展开更多
关键词 data driven vibration control(DDVC) data science designing method feedforward control industrial robot input shaping optimizing method residual vibration
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Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions 被引量:45
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作者 WANG Hong CHAI Tian-You +1 位作者 DING Jin-Liang BROWN Martin 《自动化学报》 EI CSCD 北大核心 2009年第6期739-747,共9页
关键词 自动化系统 数据分析 容错控制 故障诊断系统
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Data-driven Nonparametric Model Adaptive Precision Control for Linear Servo Systems 被引量:2
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作者 Rong-Min Cao Zhong-Sheng Hou Hui-Xing Zhou 《International Journal of Automation and computing》 EI CSCD 2014年第5期517-526,共10页
Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo... Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics. 展开更多
关键词 data-driven control nonparametric model adaptive control precision motion control permanent magnet synchronous linear motor ROBUSTNESS
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Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm 被引量:1
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作者 YUAN DONGDONG WANG YANKAI 《Journal of Shanghai Jiaotong university(Science)》 EI 2022年第6期790-798,共9页
In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor,a data driven model-free adaptive control method based on the improved slidi... In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor,a data driven model-free adaptive control method based on the improved sliding mode control(ISMC)algorithm is designed,which does not depend on the precise dynamic model of the quadrotor.The design of the general sliding mode control(SMC)algorithm depends on the mathematical model of the quadrotor and has chattering problems.In this paper,according to the dynamic characteristics of the quadrotor,an adaptive update law is introduced and a saturation function is used to improve the SMC.The proposed control strategy has an inner and an outer loop control structures.The outer loop position control provides the required reference attitude angle for the inner loop.The inner loop attitude control ensures rapid convergence of the attitude angle.The effectiveness and feasibility of the algorithm are verified by mathematical simulation.The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective,and it can effectively realize the trajectory tracking control of the quadrotor.The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle(UAV),and has high control accuracy,stability,and robustness. 展开更多
关键词 QUADROTOR trajectory tracking improved sliding mode control(ISMC) data driven model-free adaptive control
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An Improvement on Data-Driven Pole Placement for State Feedback Control and Model Identification 被引量:1
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作者 Pyone Ei Ei Shwe Shigeru Yamamoto 《Intelligent Control and Automation》 2017年第3期139-153,共15页
The recently proposed data-driven pole placement method is able to make use of measurement data to simultaneously identify a state space model and derive pole placement state feedback gain. It can achieve this precise... The recently proposed data-driven pole placement method is able to make use of measurement data to simultaneously identify a state space model and derive pole placement state feedback gain. It can achieve this precisely for systems that are linear time-invariant and for which noiseless measurement datasets are available. However, for nonlinear systems, and/or when the only noisy measurement datasets available contain noise, this approach is unable to yield satisfactory results. In this study, we investigated the effect on data-driven pole placement performance of introducing a prefilter to reduce the noise present in datasets. Using numerical simulations of a self-balancing robot, we demonstrated the important role that prefiltering can play in reducing the interference caused by noise. 展开更多
关键词 data-driven control STATE FEEDBACK POLE PLACEMENT Nonlinear Systems
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Performance Monitoring of the Data-driven Subspace Predictive Control Systems Based on Historical Objective Function Benchmark 被引量:3
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作者 王陆 李柠 李少远 《自动化学报》 EI CSCD 北大核心 2013年第5期542-547,共6页
关键词 预测控制系统 性能监控 数据驱动 子空间 历史 基准 监视控制器 目标函数
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A Data-Driven Adaptive Method for Attitude Control of Fixed-Wing Unmanned Aerial Vehicles 被引量:2
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作者 Meili Chen Yuan Wang 《Advances in Aerospace Science and Technology》 2019年第1期1-15,共15页
In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of... In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of fixed-wing unmanned aerial vehicles (UAVs). Firstly, a model-free adaptive control (MFAC) method requiring only input/output (I/O) data and no model information is adopted for control scheme design of angular velocity subsystem which contains all model information and up-mentioned uncertainties. Secondly, the internal model control (IMC) method featured with less tuning parameters and convenient tuning process is adopted for control scheme design of the certain Euler angle subsystem. Simulation results show that, the method developed is obviously superior to the cascade PID (CPID) method and the nonlinear dynamic inversion (NDI) method. 展开更多
关键词 data-driven Adaptive Method ATTITUDE control Unmanned AERIAL Vehicles (UAV) Internal Model control
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Data-Driven Process Monitoring and Fault Tolerant Control in Wind Energy Conversion System with Hydraulic Pitch System 被引量:1
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作者 王凯 罗浩 +3 位作者 KRUEGER M DING S X 杨旭 JEDSADA S 《Journal of Shanghai Jiaotong university(Science)》 EI 2015年第4期489-494,共6页
Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators an... Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators and sensors. However, despite of the hardware redundancy, sensor faults have often affected the wind turbine normal operation and thus caused energy generation loss. In this paper, aiming at the wind turbine hydraulic pitch system, data-driven design of process monitoring(PM) and diagnosis has been realized in the wind turbine benchmark. Fault tolerant control(FTC) strategies focused on sensor faults have also been presented here, where with the implementation of soft sensor the sensor fault can be handled and the performance of the system is improved. The performance of this method is demonstrated with the wind turbine benchmark provided by Math Works. 展开更多
关键词 data-driven process monitoring(PM) fault tolerant control(FTC) soft sensor wind turbine
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Data-Driven Model Identification and Control of the Inertial Systems
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作者 Irina Cojuhari 《Intelligent Control and Automation》 2023年第1期1-18,共18页
In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the sy... In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation. 展开更多
关键词 data-driven Model Identification controller Tuning Undamped Transient Response Closed-Loop System Identification PID controller
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DATA DRIVEN控制方式图象理解系统的结构性能及改进
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作者 李力 《北方工业大学学报》 1989年第3期78-82,共5页
本文是以图象理解系统实例分析入手,较详尽地论述了采用DATADRIVEN控制方式的线画解释图象理解系统的硬软件结构,并在评估了系统的可靠性基础上,提出了采用数据驱动和模型驱动双向控制的新观点.
关键词 图象理解 双向控制 结画解释
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Data-Driven Anomaly Diagnosis for Machining Processes 被引量:9
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作者 Y.C.Liang S.Wang +1 位作者 W.D.Li X.Lu 《Engineering》 SCIE EI 2019年第4期646-652,共7页
To achieve zero-defect production during computer numerical control(CNC)machining processes,it is imperative to develop effective diagnosis systems to detect anomalies efficiently.However,due to the dynamic conditions... To achieve zero-defect production during computer numerical control(CNC)machining processes,it is imperative to develop effective diagnosis systems to detect anomalies efficiently.However,due to the dynamic conditions of the machine and tooling during machining processes,the relevant diagnosis systems currently adopted in industries are incompetent.To address this issue,this paper presents a novel data-driven diagnosis system for anomalies.In this system,power data for condition monitoring are continuously collected during dynamic machining processes to support online diagnosis analysis.To facilitate the analysis,preprocessing mechanisms have been designed to de-noise,normalize,and align the monitored data.Important features are extracted from the monitored data and thresholds are defined to identify anomalies.Considering the dynamic conditions of the machine and tooling during machining processes,the thresholds used to identify anomalies can vary.Based on historical data,the values of thresholds are optimized using a fruit fly optimization(FFO)algorithm to achieve more accurate detection.Practical case studies were used to validate the system,thereby demonstrating the potential and effectiveness of the system for industrial applications. 展开更多
关键词 COMPUTER numerical control MACHINING ANOMALY detection FRUIT FLY optimization algorithm data-driven method
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金属塑性成形“材料-工艺-装备”智能化技术综述
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作者 王涛 赵文强 +3 位作者 任忠凯 刘元铭 韩建超 黄庆学 《塑性工程学报》 北大核心 2026年第2期2-31,共30页
金属塑性成形技术在现代制造业中至关重要,但传统方法在材料本构描述、工艺缺陷预测、质量优化及装备管控等方面面临精度低、效率差和适应性弱的挑战。近年来,人工智能(AI)技术的兴起为这些问题提供了创新解决方案,推动了该领域向智能... 金属塑性成形技术在现代制造业中至关重要,但传统方法在材料本构描述、工艺缺陷预测、质量优化及装备管控等方面面临精度低、效率差和适应性弱的挑战。近年来,人工智能(AI)技术的兴起为这些问题提供了创新解决方案,推动了该领域向智能化转型。系统归纳了AI技术在金属塑性成形中的应用进展,具体从材料、工艺和装备3个方面进行阐述。在材料本构方面,传统唯象模型的局限性被数据驱动方法克服,人工神经网络(ANN)提升了单一路径下的预测精度,循环神经网络(RNN)模拟复杂加载路径的历史依赖,机器学习(ML)代理模型加速微观组织动态演变预测,物理感知神经网络(PINN)与跨尺度代理模型确保热力学一致性,实现高效多尺度耦合仿真。在成形工艺中,AI通过深度学习(DL)预测宏观缺陷如起皱、回弹和微观损伤,耦合物理驱动提升鲁棒性;智能优化策略如强化学习实现厚度、板形与工艺参数的闭环控制,提高产品质量与效率。在智能装备管控中,深度学习故障诊断方法在变工况和小样本下表现出色,结合迁移学习增强泛化;剩余寿命预测与液压伺服、振动抑制的智能控制框架,支持预测性维护与自主决策。总体而言,AI显著降低了金属成形技术开发成本,明显提升了预测准确率,并在工业场景中验证了可行性。尽管面临可解释性与泛化挑战,未来通过机理-数据融合、小样本学习和数字孪生,将有效赋能金属塑性成形高质量发展。 展开更多
关键词 金属塑性成形 人工智能 数据驱动建模 智能控制 预测性维护 数字孪生
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面向建筑HVAC系统能效提升的模型预测控制方法综述
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作者 郭斌 黄孝斌 +6 位作者 李擎 黄飞 樊勇 杨永亮 王昱洁 黄超 何杰 《工程科学学报》 北大核心 2026年第3期657-670,共14页
建筑暖通空调(HVAC)是改善室内环境质量(IEQ)的关键设备,其控制技术的发展现状对于推动建筑能效的持续提升具有重要意义.为此,本文系统梳理了建筑HVAC系统控制方法的最新研究进展与前沿趋势.首先,从分离式控制及协同控制方法两个方面概... 建筑暖通空调(HVAC)是改善室内环境质量(IEQ)的关键设备,其控制技术的发展现状对于推动建筑能效的持续提升具有重要意义.为此,本文系统梳理了建筑HVAC系统控制方法的最新研究进展与前沿趋势.首先,从分离式控制及协同控制方法两个方面概述了建筑HVAC系统控制技术的主要发展历程,简述了当前在HVAC系统中广泛应用的经典模型预测控制(MPC)算法.其次,全面论述了MPC在建筑HVAC领域的四种衍生形式,包含随机MPC、分布式MPC、数据驱动MPC以及MPC与强化学习的融合方法.最后,从算法可迁移性与实时性、多时间尺度控制等方面讨论了四种MPC衍生形式存在的技术瓶颈,并指出了其在知识迁移与自适应学习、混合智能控制等方面的发展趋势. 展开更多
关键词 建筑暖通空调系统 模型预测控制 数据驱动 强化学习 发展趋势
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基于陷波抗停滞的永磁同步电机无模型预测电流滑模控制 被引量:1
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作者 魏尧 付俊荣 +1 位作者 王高林 汪凤翔 《电工技术学报》 北大核心 2026年第2期475-486,共12页
无模型预测滑模控制(SMC)通过建立数据模型,实现对物理模型及参数的完全独立。但建模和更新过程对采样数据质量提出严格的要求,停滞及其负面影响成为制约技术发展的关键瓶颈。针对该问题,该文提出基于陷波抗停滞的永磁同步电机(PMSM)无... 无模型预测滑模控制(SMC)通过建立数据模型,实现对物理模型及参数的完全独立。但建模和更新过程对采样数据质量提出严格的要求,停滞及其负面影响成为制约技术发展的关键瓶颈。针对该问题,该文提出基于陷波抗停滞的永磁同步电机(PMSM)无模型预测电流滑模控制方法。该方法通过设计陷波结构,提取由控制策略产生的特定频段谐波,并反向注入采样数据,生成数据梯度,旨在有效减少停滞发生的可能性并缓解停滞效应造成的不良影响,确保数据模型的高度适配。在理论层面对方法可达性、稳定性及鲁棒性进行深入分析。实验表明,相较于比较控制方法,所提方法在电流质量和预测精度方面具有优势,为PMSM在复杂环境下的高性能控制提供了新的有效途径。 展开更多
关键词 无模型预测滑模控制 陷波抗停滞部分 数据驱动模型 永磁同步电机
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基于谱子流形数据驱动建模的输流管道非线性振动主动控制
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作者 王迪之 沈聪 +1 位作者 王琳 李明武 《力学学报》 北大核心 2026年第1期194-207,共14页
输流管是工程领域中的一种典型流固耦合系统,当管内流速增大时,流体惯性力、黏性力与管道结构弹性力之间的相互作用会诱发丰富的动力学行为,可造成结构失稳和大幅的非线性振动,须对此类非线性振动进行控制以确保管路系统服役安全.主动... 输流管是工程领域中的一种典型流固耦合系统,当管内流速增大时,流体惯性力、黏性力与管道结构弹性力之间的相互作用会诱发丰富的动力学行为,可造成结构失稳和大幅的非线性振动,须对此类非线性振动进行控制以确保管路系统服役安全.主动控制以系统模型为基础,是结构非线性振动抑制的有力手段,但输流管系统面临高维强非线性和边界复杂等难点,对其进行低维建模较为困难.针对此问题,本文提出基于谱子流形的数据驱动方法对输流管道进行建模并进行振动控制.该方法通过记录输流管系统的响应,使用记录的数据来学习系统的谱子流形及降阶自治动力学模型,再通过带控制的动态模态分解或长短期记忆神经网络修正自治模型从而获得计入控制的低维模型,最终通过线性二次型调节器或模型预测控制来获得最优输入,以实现管道的振动控制.通过不同边界和流速下管道的非线性振动抑制验证了该方法的有效性,成功实现了屈曲及颤振失稳的抑制和混沌运动的控制. 展开更多
关键词 数据驱动 谱子流形 主动控制 输流管
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基于阶跃脉冲调制的无线电能传输逆变器建模与控制
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作者 刘姜涛 邓其军 张镕蓉 《湖北第二师范学院学报》 2026年第2期12-20,共9页
传统移相控制下,无线电能传输(Wireles power transfer,WPT)系统输出功率宽范围调节时逆变器开关管易丢失零电压开关(Zero voltage switching,ZVS)状态,导致逆变器切换损耗增大甚至损坏。阶跃脉冲调制(Stepped Pulse Modulation)是一种... 传统移相控制下,无线电能传输(Wireles power transfer,WPT)系统输出功率宽范围调节时逆变器开关管易丢失零电压开关(Zero voltage switching,ZVS)状态,导致逆变器切换损耗增大甚至损坏。阶跃脉冲调制(Stepped Pulse Modulation)是一种低输出纹波调制方法,可实现宽负载范围内的ZVS运行。但是,该调制方法包含有限状态机等环节,不易采用传统的机理建模访求进行建模,给控制器设计带来困难。在Simulink电路的基础上,基于数据驱动方法辨识了无线电能传输在阶跃脉冲调制下传递函数模型,并基于该模型设计内模控制器。实验表明,基于Simulink电路仿真方法获取采样数据,能够有效解决实物实验在某些场景下难以获取实验数据的难题,获得满意的辨识模型。同时,基于辨识模型设计的内模控制器,能够精确估计不同控制参数下的系统控制性能,满足了阶跃脉冲调制无线电能传输输出电压闭环控制的性能需求。 展开更多
关键词 脉冲密度调制 无线能量传输 零电压开关 数据驱动建模 内模控制器
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基于模型-数据混合驱动的配电网线损异常诊断方法
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作者 艾渊 李家浩 +3 位作者 孙立元 刘兴龙 张益鸣 杨昊 《电测与仪表》 北大核心 2026年第1期115-122,共8页
线损包括技术线损和非技术线损,是电网经济运行的重要技术指标。针对当前线损异常检测中标记样本较少,难以确定异常位置的问题,文中提出了基于数据混合驱动的异常诊断方法,包含三个阶段:异常馈线检测、异常时段检测和异常位置检测。在... 线损包括技术线损和非技术线损,是电网经济运行的重要技术指标。针对当前线损异常检测中标记样本较少,难以确定异常位置的问题,文中提出了基于数据混合驱动的异常诊断方法,包含三个阶段:异常馈线检测、异常时段检测和异常位置检测。在异常馈线检测阶段,先进行异常馈线检测特征提取,当标记样本不足时,采用聚类算法进行检测,积累足够的标记样本后,采用分类算法进行检测,提高准确率;在异常时段检测阶段,引入X-bar控制图理论,将超出控制上下限的时段判定为异常时段;在异常位置检测阶段,构建了三个风险指标,并基于此提出了变压器风险等级判定准则,定位异常位置。最后,基于实际运行数据进行仿真分析,验证了文中方法的正确性和有效性。 展开更多
关键词 线损 异常诊断 数据驱动 聚类算法 X-bar控制图
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