SNR2

说明：  此文件包是自动实习图像配准的matlab源码，同时可以显示图像翘曲和仿射的效果。(This training package is automatically matlab source code image registration, and can display images and affine warping effects.)

说明：  研究基于粒子群算法控制系统PID参数优化设计方法以及对PID控制的改进。( study the optimal design of PID parameter of the control system based on Particle Swarm Optimization and find a way to improve the PID control. )

对于单级的机械臂，运动包括刚性转角和柔性振动，程序通过标准的LQR输出和状态控制实现其调节器功能(For a single robotic arm, the campaign includes a rigid corner and flexible vibration, and program control through a standard LQR output and status to achieve their regulator function)

基于杂交的粒子群优化函数--借鉴遗传算法的杂交概念，在每次迭代中，根据杂交概率选取指定数量的例子放入杂交池中，里面的例子随机两两杂交，产生相同数目的子代例子(Hybridization-based particle swarm optimization functions- Reference hybrid genetic algorithm concepts, in each iteration, according to the selected crossover probability into a specified number of examples of hybrid pool, examples of which twenty-two random hybridization, the same number of offspring produced example)

fuzzy pid control motor

this is a very interesting paper, ple read it TransmitAntennaSelectionSchemeswith ReducedFeedbackRate, I will upload source code later. I am finding it in my computer

QR分解-householder reflection(householder reflection)

MATLAB code to Import a gray scale image Decompose it into two-three sub bands,Reconstruct the original image the different subbands

介绍matlab在控制过程中的应用。They are designed to help you learn how to use Matlab for the analysis and design of automatic control systems.(Matlab introduction in the control process applications. They are designed to help you learn how to use Matlab for the analysis and design of automatic control systems.)

一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。(A comparison based on the threshold criteria for the particle to handle multi-objective constrained optimization problem, part of the guidelines can keep order value is small and the constraint violation in allowing infeasible solutions within the particles, so as to achieve a feasible solution to the infeasible solution The purpose of evolution a new function of crowding, making the Pareto front in the sparse region and near the border points have a greater value of the congestion function, which is the larger the probability of selection so as to constitute solve multi-objective constrained optimization problems hybrid particle swarm algorithm.)