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Description: 建立了一级倒立摆的状态空间模型，并采用LQR实现了稳定控制。-establishment of an inverted pendulum of state space models, and the use of LQR achieve stability control.
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Author: jiangsx |
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Description: 状态空间模型 加强ＭＡＴＬＡＢ学习 很有用的
-state-space model to strengthen MATLAB very useful learning
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Author: 龙腾 |
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Description: In this article, we present an overview of methods for sequential simulation from posterior distributions.
These methods are of particular interest in Bayesian filtering for discrete time dynamic models
that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed
that unifies many of the methods which have been proposed over the last few decades in several
different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin
particular how to incorporate local linearisation methods similar to those which have previously been
employed in the deterministic filtering literature these lead to very effective importance distributions.
Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of
the analytic structure present in some important classes of state-space models. In a final section we
develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
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Author: 阳关 |
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Description: 使用VB语言实现的卡尔曼滤波源程序，
其基本思想是：采用信号与噪声的状态空间模型，利用前一时刻地估计值和现时刻的观测值来更新对状态变量的估计，求出现时刻的估计值。它适合于实时处理和计算机运算。
-The use of VB language source realize the Kalman filter, the basic idea is: the use of signal-to-noise state-space model, one time use of the former and current estimated value of the observed values at all times to update the estimate of state variables, and emerged moments estimated value. It is suitable for real-time processing and computing.
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Author: 张平 |
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Description: 卡尔曼滤波算法C++，采用信号与噪声的状态空间模型，利用前一时刻地估计值和现时刻的观测值来更新对状态变量的估计，求出现时刻的估计值。-Kalman filter algorithm C++, The use of signal and noise of the state space model, using the previous estimate of the value of time and is now time to update the observations of the estimated state variables, and the estimated value of moment occurred.
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Author: wltwang |
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Description: 现代控制理论基础
高等工科院校控制类课程系列化教材:本书内容包括：控制系统的状态空间描述、线性控制系统分析、状态反馈与状态观测设计等。-Modern control theory based on control engineering colleges teaching courses serialization: this book include: control system state-space description of linear control systems analysis, state feedback and state observer design.
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Author: 宫晓春 |
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Description: 将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析.基于平滑先验约束的概念，使用卡尔曼滤波和赤池的AIC方法拟合全局模型，得到陀螺漂移模型的若干数值结果并用于陀螺系统分析.由于观测序列的趋势项、不规则分量可同时建模，因此比分别建模在统计上更加准确有效.-Will be non-stationary time series state space modeling method for the analysis of the transition process gyro. Priori smoothness constraint based on the concept, the use of Kalman filtering and Akaike s AIC method of fitting the overall model, the gyro drift model and a number of numerical results in the gyro system analysis. Due to the trend observed sequence, the irregular component may be at the same time modeling, modeling than were statistically more accurate and effective.
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Author: 我爱 |
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Description: documentation for optimal filtering toolbox for mathematical software
package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter
and unscented Kalman filter for discrete time state space models. Also included in the toolbox
are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which
can be used to smooth the previous state estimates, after obtaining new measurements. The usage
and function of each method are illustrated with five demonstrations problems.
1-documentation for optimal filtering toolbox for mathematical softwarepackage Matlab. The methods in the toolbox include Kalman filter, extended Kalman filterand unscented Kalman filter for discrete time state space models. Als
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Author: eestarliu |
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Description: MATLAB语言实现的模糊控制，参数可调，被控对象输入方式有传函、零极点、状态空间。是对被控对象的软计算。-MATLAB language of fuzzy control, adjustable parameters, was charged with the importation of the way the target transfer function, zero-pole placement, state-space. The object of soft computing.
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Author: 林坤 |
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Description: The state space model is nonlinear and is input to the function along with the current measurement. The function performs the extended Kalman filter update and returns the estimated next state and error covariance
MATLAB 7.6 (R2008a)
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Author: Rafal |
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Description: 详细介绍了基于状态空间模型的控制系统设计，包括极点配置的各种方法-Described in detail based on the state space model of control system design, including various methods of pole placement
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Author: 魏雪漫 |
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Description: The state space model is nonlinear and is input to the function along with the current measurement. The function performs the extended Kalman filter update and returns the estimated next state and error covariance
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Author: sofi |
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Description: state space model - john aston
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Author: drbrownisback |
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Description: good sources of knowledge to know about state space analysis of control systems
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Size: 311296 |
Author: ssssss |
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Description: state space model of system sampling time
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Size: 9216 |
Author: ali |
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Description: 书名：现代控制引论教程 Matlab辅助实验
本教材共9章。第1章介绍了经典控制论的主要内容，这是研究控制论问题时最初引入的理论和方法；第2章是现代控制论采用的状态空间描述，包括连续时间和离散时间空间模型；第3章是系统状态分析；第4章介绍了现代控制论的两个标志性的内容．即系统状态的能控性和能观性，以及能控性和能观性的判定等内容；第5章介绍了系统各种稳定性的概念和判别方法；第6章是在前5章分析的基础上，讨论了系统综合问题，如极点配置、镇定等；第7章介绍了最优控制的基本方法——极小值原理和动态规划法；第8章和第9章分别对控制论的两个分支：随机系统的状态滤波与控制和自适应控制方面等内容作了基本介绍。
-Title: Introduction to modern control experiment textbook tutorial of Matlab including 9 Chapters:
Chp1 introduces the main content of classical control theory, cybernetics is the study of this problem first introduced the theory and methods in Chp2 of the modern control theory using state-space description, including the continuous time and discrete time space model
Chp3 is the system state analysis
Chp4 describes the modern control theory, the two iconic content. The state of the system controllability and observability and controllability and observability of the decision, etc. Chp5 introduces the concept of system stability and discrimination of various methods
Chp6 is based on the former 5 chapters and discusses the systems integration issues, such as pole placement, stabilization, etc.
Chp7 describes the basic method of optimal control- minimum principle and dynamic programming
Chp8 and 9, respectively, on control theory The two branches: the state of stochastic
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Author: 商志远 |
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Description: 基于状态空间被控对象的含有时滞的预测控制算法的一个求解LMI的例子-Controlled object based on state space predictive control algorithm with delay a case for solving LMI
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Author: zhangjunling |
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Description: 混沌系统的相空间重构，可用于分析庞加莱截面-reconstruction of state space
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Size: 106496 |
Author: gaofei |
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Description: 通过建立状态空间模型，使用simulink仿真，其中包括了kalman滤波-Through the establishment of the state space model, using the simulink simulation, including the kalman filter
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Size: 24576 |
Author: xiaoming |
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Description: linear state-space control systems course
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Author: pitson |
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