LLC

说明：  蚁群算法用来函数寻优，本代码给出了通用版本，能够很好的适应和学习(Ant colony algorithm is used to function optimization, this code gives a general version, can adapt and learn well)

说明：  基于SVPWM的电压型三相整流仿真系统，包括SVPWM模块，以及电流环和电压环的建模(The simulation system of voltage source three-phase rectifier based on SVPWM includes SVPWM module, modeling of current loop and voltage loop)

基于交流电机动态方程，编写Matlab分析程序，用于交流电机动态分析。(Based on the dynamic equation of AC motor, Matlab analysis program is written for dynamic analysis of AC motor.)

腹板式渐开线直齿圆柱齿轮建模,利用ANSYS软件模拟，能很容易得到应力分布(Modeling of web type involute spur gear)

说明：  计算可见光通信中最大化最小速率的优化问题，还有稳健波束成形(The optimization problem of maximizing the minimum rate and robust beamforming are also discussed)

实现有源电力滤波器的电流跟踪控制，能够代替传统PI控制策略(Active power filter current tracking control can replace the traditional PI control strategy)

一个基于二阶广义积分器的锁相环仿真模型，可以测得三相正弦信号的相位和频率(Phase-locked loop simulation model based on Nikai Hiroyoshi integrator)

说明：  完成对四旋翼飞行器的数学建模，并在matlab矩阵实验室中进行仿真，进一步设计飞行控制系统。(Complete the mathematical modeling of quadrotor aircraft, and simulate in MATLAB matrix laboratory.)

高压共轨系统模型，包括喷油器，油泵，共轨(High pressure common rail system model, including injector, oil pump, common rail)

大坝变形的精确预测对其安全评价方面发挥着重要作用。为了进一步提高大坝变形预测精度，提出了一种改进的灰狼算法优化支持向量机的预测模型。通过引入非线性收敛因子和采用动态加权策略，提升灰狼算法优化支持向量机惩罚因子和核函数参数的能力，并以优化的参数来建立支持向量机大坝变形预测模型。选取实例数据，在与布谷鸟算法、差分进化算法、粒子群算法、基本灰狼算法优化的支持向量机预测比较中，实验结果表明，改进的灰狼算法对支持向量机参数的优化是有效的，可以提高大坝变形预测精度。(Accurate prediction of dam deformation plays an important role in its safety evaluation. In order to further improve the prediction accuracy of dam deformation, an improved grey Wolf algorithm is proposed to optimize the prediction model of support vector machine. By introducing the nonlinear convergence factor and using the dynamic weighting strategy, the gray wolf algorithm is improved to optimize the capacity of the support vector machine penalty factor and the kernel parameter, and the support vector machine dam deformation prediction model is established with the optimized parameters. The experimental results show that the Improved Grey Wolf algorithm is effective for the optimization of support vector machine parameters, and it can improve the accuracy of the deformation prediction of the dam.)