state-estimation-module

本文 是 基于MATLAB的滤波器的设计(This article is based on the MATLAB filter design)

线性化反馈的自适应模糊滑模控制 详细的程序和simulink图 希望对大家有帮助(the code of liner feedback and fuzzy sliding mode)

万挂作坊工具箱[100914] 窗口,键码,颜色,光标,消息,进程分析工具(Toolbox hanging workshop million [100914] window, key code, color, cursor, news, process analysis tools)

说明：  粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 PSO模拟社会采用了以下三条简单规则对粒子个体进行操作：①飞离最近的个体，以避免碰撞。②飞向目标。③飞向群体的中心。这是粒子群算法的基本概念之一。 粒子群算法其基本思想是受许多鸟类的群体行为进行建模与仿真研究结果的启发(Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values ​ ​ of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori)

floyd算法产生矩阵读出算法，能够读出路由矩阵(floyd algorithm to generate matrix read out algorithm, able to read way by the matrix)

说明：  这是黑龙江大学自控理论杨易朋同学在最优估计课程当中用matlab编写的递推增广最小二乘算法!(This is the theory of Heilongjiang University, Yang Yi-controlled peer students in courses optimal estimate prepared by using Matlab recursive least squares algorithm to broaden!)

案例2 BP神经网络的非线性系统建模-非线性函数拟合(The BP neural network of nonlinear system modeling-nonlinear function fitting)

整体最小二乘迭代法的matlab实现，其与奇异值分解法是等价的(The total least squares iterative method of Matlab implementation, and the singular value decomposition method is equivalent )

绘分形树：tree(n,a,b),n为分形树迭代次数 a,b为分枝与竖直方向夹角 (Painted fractal tree)

最优化求函数迭代有牛顿法。0.618.等(Demand function optimization iteration Newton method. 0.618.)