MVT_v1_0

交流位置伺服系统因其存在参数时变、负载扰动以及电机的非线性等缺点， 很难为其建立准确的模型. 模糊（ fuzzy）控制具有无需建立被控对象的数学模型、鲁棒性好等 优点，但稳态精度差. 将模糊控制和PID 控制相结合，设计了Fuzzy-PID 双模控制器. 在论域内 用不同的控制方式分段实现控制，这样就综合了模糊控制和PID 控制的优点，克服了各自的缺 点. 该控制器结构简单、易于实现. 在半闭环交流位置伺服系统上所做的实验表明，采用Fuzzy- PID 双模控制器与采用经典PID 控制器相比，阶跃响应的调整时间减少了33. 7 ，并且无超 调，轨迹跟踪误差减小了47. 2 .(AC servo system because of the presence of parameter variations, load disturbances and non-linear motors and other shortcomings, it is difficult to establish accurate models for fuzzy (fuzzy) control without having to build a mathematical model of controlled object, robustness and good However, steady-state accuracy is poor. fuzzy control and PID control are combined to design a dual-mode Fuzzy-PID controller in the sub-region to achieve control on the different control methods, so that a combination of fuzzy control and PID control advantages to overcome their disadvantages. simply the controller structure, easy to implement. experiments on semi-closed loop AC servo system did show that the Fuzzy-PID controller is compared with the classic dual-mode PID controller, step response The adjustment time is reduced by 33.7 , and no overshoot, tracking error is reduced 47.2 .)

拉普拉斯特征映射,最大差异展开，时频域特征(Laplacian Eigenmap Maximum difference expansion Fast Maximum difference expansion ISOMAP)

说明：  蚁群算法的改进 在MATLAB中可以直接仿真 研究这方面的可以好好间就一下((Ant colony algorithm is improved))

power system optimization

pso解决tsp问题 matlab源码 可做为学习参考(pso to solve the problem tsp matlab source code can be used as study and reference)

patchantenna matlab code

说明：  混沌时间序列特征，G_P算法，求关联维，matlan(Characteristics of chaotic time series, G_P algorithm, and correlation dimension, matlan)

说明：  在matlab环境下仿真实际弱目标的运动状况，利用差分得到实际目标的真实轨迹。(Matlab simulation environment in the actual movement of the weak state of the target, using the actual goal differential has been the true trajectory.)

本程序源码是为日本一家地震监测机构编写的，用来演示地震对不同楼层的作用效果。可以手动调整震动幅度的比例。(the program source code is one of Japan's earthquake monitoring bodies to prepare, used to demonstrate the different floors of the earthquake in effect. Vibration can be manually adjusted rate ratio.)

Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.