Single-Loop-DC-Motor-System

自己编的EMODEL 的matlab程序，希望对大家有帮助!多指正!谢谢!(Own EMODEL of the matlab program, and they hope to help you! More correction! Thank you!)

这是清华大学出版社的Matlab工程数学应用丛书。是对MATAB更深层次的应用。(This is the Matlab Tsinghua University Press Mathematics Applied Engineering Series. Is MATAB deeper applications.)

新加入条件属性对决策属性的依赖度计算函数。基于粗糙集。(The new conditions for accession to the decision attribute attribute dependency calculation functions. Based on rough sets.)

说明：  上转型对象 1．实验目的 掌握上转型对象的使用。 2． 实验要求 要求有一个abstract类，类名为Employee，Employee的子类有YearWorker、MonthWorker和WeekWorker。YearWorker对象按年领取薪水，MonthWorker按月领取薪水，WeekWorker按周领取薪水。Employee有一个abstract方法： public abstract earnings() 子类必须重写父类的earnings()方法，给出各自领取薪水的具体方式。 有一个Company类，该类用Employee数组作为成员，Employee数组的单元可以是YearWorker对象、MonthWorker对象或WeekWorker对象的上转型对象。程序能输出Company对象一年需支付的薪水总额。 (The transformation of the object 1. Purpose of the experiment used to grasp the transformation of the object. 2. Experiment requires a abstract class requirements, class named Employee, Employee of the child class has YearWorker, MonthWorker and WeekWorker. YearWorker object to receive annual salary, MonthWorker receive a monthly salary, WeekWorker receive weekly salary. Employee one abstract method: public abstract earnings () sub-class must override the parent class of earnings () method, given their own specific way of receiving pay. A Company class, such as members with an array of Employee, Employee of the array elements can be YearWorker object, MonthWorker object or objects on the transformation of objects WeekWorker. Company object program can output a year' s salary to be paid the total amount.)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数(Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets)

Kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping.

车式移动机器人圆形轨迹跟踪控制程序，是利用MATLAB做的，还有控制图(Round the car-type mobile robot trajectory tracking control procedures)

Applying postureidentifierindesigninganadaptivenonlinearpredictive controller fornonholonomicmobilerobot

说明：  ukf与ekf做对比，可以看出ufk与ekf的性能差别(compare ukf with ekf)

经改进的希尔伯特——黄分解，效果不错，在MATLAB中实现(Improved Hilbert- Huang Decomposition, good results in MATLAB to achieve)