搜索资源列表
bp.pso.rar
- 标准BP神经网络算法程序:动量BP算法程序:% 调用 TRAINGDX 算法训练 BP 网络 粒子群优化神经网络源程序,The standard BP neural network algorithm procedure: momentum BP algorithm procedure: TRAINGDX called BP network training algorithm particle swarm optimization neural network source code
PSOGABPDRNN.rar
- 此包含有遗传算法、粒子群算法、BP算法优化对角递归神经网络的MATLAB程序,This includes genetic algorithms, particle swarm optimization, BP algorithm for diagonal recurrent neural network of the MATLAB program
POS-PID
- 运用粒子群优化算法对PID控制器进行优化设计,通过matlab实现-The use of particle swarm optimization algorithm to optimize the design of PID controller, through matlab to achieve
tunning_PID_by_PSO
- 粒子群优化算法。PID控制器的整定,matlab源码。-Tunning of PID controller using Particle Swarm Optimization Author: Wael Mansour (wael192@yahoo.com) MSc Student, Electrical Enginering Dept, Faculty of Engineering Cairo University, Egypt
tunning-PID-by-PSO
- 粒子群优化PID的典型例子,调试过了,非常好用-Particle Swarm Optimization typical example of the PID, debugging, and very easy to use
粒子群PID
- 该代码为基于pso算法优化的PID神经网络的系统控制算法(The code is based on the PSO algorithm optimized PID neural network system control algorithm)
利用PSO算法优化求解PID参数
- PSO粒子群优化的PID参数,通过matlab平台C语言来编写,达到优化控制的目的(PSO particle swarm optimization PID parameters, through the MATLAB platform C language to write, to achieve the purpose of optimization control)
基于粒子群算法的PID控制器优化设计
- matlab智能算法,基于粒子群算法的PID控制器优化设计(Matlab intelligent algorithm, particle swarm optimization based PID controller optimization design)
chapter14基于粒子群算法的PID控制器优化设计
- chapter15基于混合粒子群算法的TSP搜索算法(A TSP Search Algorithm Based on Hybrid Particle Swarm Optimization)
chapter14 基于粒子群算法的PID控制器优化设计
- chapter14 基于粒子群算法的PID控制器优化设计,粒子群算法也是个不错的优化参数算法(chapter14 Particle swarm optimization algorithm based on PID controller design, Particle Swarm Optimization algorithm is also a good optimization algorithm)
PID+ PSO
- 通过粒子群算法优化PID控制中的一些参数,(Some parameters in PID control are optimized by PSO.)
新建文件夹
- 粒子群算法PID,利用粒子群算法优化PID参数,simulink,代码(Particle swarm optimization (PID), using particle swarm optimization (PSO) to optimize PID parameters, Simulink, code)
粒子群算法优化PID参数实例1
- 粒子群算法优化PID参数实例+matlab代码学习研究(Optimization of PID parameters by particle swarm optimization)
PSO-PID参数
- 利用标准粒子群算法优化PID参数,用以控制直流电机模型(The standard particle swarm optimization (PSO) algorithm is used to optimize the PID parameters to control the DC motor model)
粒子群优化算法
- 用粒子群优化算法对三轴稳定航天器姿态控制PD参数进行自动寻优(optimization of PD parameter of attitude controller in spacecraft)
基于粒子群算法和遗传算法的PID参数优化
- 基于粒子群算法和遗传算法的PID参数优化程序和相应文档(The Optimization of PID Parameters Based on Particle Swarm Optimization and Genetic Algorithm)
AIPSO
- 免疫粒子群混合优化算法整定PID,该方法将免疫算法中的基于浓度的抗体繁殖策略 与粒子群优化算法相结合。对浓度低的粒子进行促进,对浓度高的粒子进行抑制,因而保持了粒子的多样性,克服了PSO 算法易于陷入局部最优点的缺点,寻优速度快。(PID paramaters optimization by AIPSO)
chapter14 基于粒子群算法的PID控制器优化设计
- 利用粒子群算法对PID参数进行优化,有利于初学者的学习和参考。(Using particle swarm optimization to optimize the parameters of PID is beneficial to beginners'learning and reference)
PSO的PID控制器
- 针对一般的粒子群优化(PSO)学习算法中存在的容易陷入局部最优和搜索精度不高的缺点,对改进型PSO算法进行研究。由于惯性权重系数ω对算法是否会陷入局部最优起到关键的作用,因此,通过改变惯性权重ω的选择,对惯性权重系数采取线性减小的方法,引入改进型的PSO算法。采用改进的PSO算法对PID控制器进行参数优化并把得到的最优参数应用于控制系统中进行仿真。仿真实验结果表明:改进型PSO算法不会陷入局部最优,能得到全局最优的PID控制器的参数,并使得控制系统的性能指标达到最优,控制系统具有较好的鲁棒性。(
粒子群算法优化pid源码 matlab仿真
- 粒子群算法(PSO)整定pid控制参数,比传统Z-N整定方法要好,内附matlab程序与simulink模型(Particle swarm optimization (PSO) is better than traditional Z-N tuning method in tuning PID control parameters. It includes matlab program and Simulink model.)