搜索资源列表
UKF
- 从改进提议分布的成片野值容错能力入手，提出了基于残差正交判别的UPF容错滤波算法，该算 法将残差正交判别法UKF的野值自适应性和粒子滤波的“适者生存性”有机地结合起来．通过非线性状态估计 的实验，证实了这种新的自适应粒子滤波对成片野值处理的有效性，-Proposal from the improved value of the distribution of fault tolerance into the film field, put forward an identificatio
distribution-power-system
- 配电系统潮流计算及状态估计,详细介绍了配电系统中潮流计算的软件设计流程及状态估计算法-distribution power flow and state estimation
PatternClassification.pdf
- Nonlinear Sequential State Estimation for Solving PatternClassification Problems
PSO
- 关于PSO智能算法在多率系统的状态和参数估计中的应用-PSO intelligent algorithm in multi-rate system of state and parameter estimation
n-bus-Power-Flow-Solver-1
- DEscr iptION: This Matlab algorithm performs many tasks associated with power system analysis. First, it has the ability to perform both fully coupled and dc power flow analysis. Second, it has the ability to create measurements (with user-
n-bus-Power-Flow-Solver-2
- DEscr iptION: This Matlab algorithm performs many tasks associated with power system analysis. First, it has the ability to perform both fully coupled and dc power flow analysis. Second, it has the ability to create measurements (with user-
n-bus-Power-Flow-Solver-4
- DEscr iptION: This Matlab algorithm performs many tasks associated with power system analysis. First, it has the ability to perform both fully coupled and dc power flow analysis. Second, it has the ability to create measurements (with user-
Particle-filter-resampling-methods
- 粒子滤波是基于递推的MonteCarlo仿真方法的总称, 原则上可用于任意非线性、非高斯随机系统的状态估计。-Particle filter is based on the the MonteCarlo simulation method of recursive general principle can be used for any nonlinear, non-Gaussian random system state estimation.
Particle-filter-algorithm-
- 粒子滤波是基于递推的蒙特卡罗模拟方法的总称，可用于任意非线性，非高斯随机系统的状态估计。-The particle filter is based on recursive Monte Carlo simulation method general, can be used for any non-linear, non-Gaussian random system state estimation.
paixu
- 用于在配电网状态估计之前对一定数量的测量装置在配电网中进行最优安装。-On a number of measuring devices used for state estimation of the distribution network in the distribution network for optimal installation.
8.7-state-estimation
- satate estimation in power systeme
5
- The doubly fed induction generator (DFIG) is widely used in wind energy. This paper proposes a model-based predictive controller for a power control of DFIG. The control law is derived by optimization of an objective function that considers the
Multi-UAVs-Target-Tracking
- 多无人机（Unmanned Aerial Vehicle，UAV）协同目标跟踪在军/民用方面有 着广泛而又迫切的应用需求和重要的理论研究价值，是目前多 UAV 系统自主控制 领域的一个重要研究方向。本文以 UAV 执行对地侦察打击任务为应用背景，针对 复杂环境中多 UAV 协作式跟踪地面移动目标问题，重点围绕目标状态融合估计和 观测航迹优化两项关键内容展开研究-Multi-UAV (Unmanned Aerial Vehicle, UAV) has a broad and col
Matlab
- 卡尔曼滤波器是一个对动态系统的状态序列进行线性最小误差估计的算法，一般用于线性系统。一般在运动跟踪领域中摄像机相对于目标物体运动有时属于非线性系统，但由于在一般运动跟踪问题中图像采集时间间隔较短，可近似将单位时间内目标在图像中的运动看作匀速运动，采用卡尔曼滤波器可以实现对目标运动参数的估计。-Kalman filter is a state sequence of linear dynamic systems smallest error estimation algorithm for lin
03thesis
- A Fuzzy-Kalman Filtering Strategy for State Estimation
电池SOC估算
- 电池荷电状态的估算是电池管理系统的核心内容估算准确与否,将直接影响到电池管理系统的决策和控制。在结合开路电压法、安时法的基础上。充分利用扩展卡尔曼滤波法的修正功能综合考虑电池充放电倍率、温度和充放电循环次数等因素对电池的影晌,提出了卡尔曼滤波修正算法,并将其应用在插电式混合动力汽车电池管理系统中。(The estimation of battery charge state is the core content of battery management system. Whether th