Search - pso_pid

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[Other resource] pso_pid DL : 1: 这是个利用粒子群算法(PSO)优化PID控制器参数的matlab程序，其中选取的性能指标为ITAE。-this is the use of particle swarm algorithm (PSO) PID controller optimized parameters of Matlab procedures, these performance indicators selected for ITAE.
Update : 2008-10-13 Size : 1.84kb Publisher : jiangsx
[Other resource] pso_pid DL : 0: 用混沌微粒子算法整定PID控制器matlab的代码
Update : 2008-10-13 Size : 1.29kb Publisher : 江明
[Other] PSO_PID DL : 0: 利用PSO粒子群搜索算法,辨识PID参数:Kp,Ki,Kd.结果表明虽然该方法辨识精度不是很高,但是也有一定可信度.
Update : 2008-10-13 Size : 3.4kb Publisher : kpg
[matlab] pso_pid DL : 1: 这是个利用粒子群算法(PSO)优化PID控制器参数的matlab程序，其中选取的性能指标为ITAE。-this is the use of particle swarm algorithm (PSO) PID controller optimized parameters of Matlab procedures, these performance indicators selected for ITAE.
Update : 2025-02-17 Size : 2kb Publisher : jiangsx
[matlab] pso_pid DL : 0: 用混沌微粒子算法整定PID控制器matlab的代码-Chaos particles with PID controller tuning algorithm matlab code
Update : 2025-02-17 Size : 1kb Publisher : 江明
[Other] PSO_PID DL : 1: 利用PSO粒子群搜索算法,辨识PID参数:Kp,Ki,Kd.结果表明虽然该方法辨识精度不是很高,但是也有一定可信度.-Use english PSO Particle Swarm algorithm, identification of PID parameters: Kp, Ki, Kd. The results show that although the method is not very high recognition accuracy, but it also has a certain credibility.
Update : 2025-02-17 Size : 3kb Publisher : kpg
[matlab] 49636960PSO_PID DL : 0: 基于粒子群算法的PID参数设置。其中程序比较先进。-Particle Swarm Optimization Based on the PID parameters. One of the more advanced procedures.
Update : 2025-02-17 Size : 3kb Publisher : 尹小峰
[VC/MFC] 73462660pso_pid DL : 0: This family reference manual section is meant to serve as a complement to device data sheets. Depending on the device variant, this manual section may not apply to all dsPIC33F/PIC24H devices.
Update : 2025-02-17 Size : 1kb Publisher : SeoYoungNam
[matlab] pso_pid DL : 0: pid design by pso algorithm
Update : 2025-02-17 Size : 1kb Publisher : javad
[matlab] PSO_PID DL : 0: 免疫粒子群算法用于PID整定。采用线性惯性系数，自适应交叉变异方法-AI-pso for PID tune.Using a linear inertial coefficient, adaptive crossover and mutation methods
Update : 2025-02-17 Size : 2kb Publisher : 珠泪
[Other] PSO_PID DL : 0: 出了一种PID控制器参数整定的粒子群优化算法。该方法首先通过定叉一个包含系统超调量J二升时间和稳态误差指标项的适应度函数，并根据系统的实际控制要求时各指标项适当加权。之后由带收缩因子的粒子群算法时PID进行多目标手优，从而实现PID控制器的自动参数整定。仿真结果表明，该方法优化得到P1D控制器的综合性能优于常规方法得到的PID控制器。-particle swanll optimization algorithms for parameter tuning of PID controlIers is proposed First，a fitness function which includes some terms represent overshoot．im time and steady error of the system is defined．and the terrtls m weighted properly Then the particle swarm optimization algorithms with a constriction factor is used for multi-objective optimization of PID controllers，and the auto parameter tuning of HD controllers carl be realized Simulation results show that the synthesized perfurmanee of PID contro]lers obtained by the proposed method superior to that by standard methods
Update : 2025-02-17 Size : 237kb Publisher : dhskja
[AI-NN-PR] pso_pid DL : 1: 基于粒子群算法分数阶PID参数整定，运行环境是matlab2007-Based on particle swarm optimization (pso) algorithm of fractional order PID parameter setting
Update : 2025-02-17 Size : 4kb Publisher : 孟庆涛
[matlab] PSO_PID DL : 0: 使用Simulink环境建立的基于PSO的PID控制器的优化设计。其中PID_Model为控制系统模型 PSO为PSO部分程序实现 PSO_PID为PSO优化PID的过程 -Use Simulink environment to establish optimal design of PID controller based on PSO. Model for the control system which PID_Model PSO PSO as part of the program to achieve PSO_PID PID optimization process for PSO
Update : 2025-02-17 Size : 9kb Publisher : zhang yy
[matlab] pso_pid DL : 0: 利用粒子群算法对 PID 控制器的参数进行优化设计-Using particle swarm optimization algorithm to optimize the parameters of PID controller
Update : 2025-02-17 Size : 9kb Publisher : 董事
[matlab] PSO_PID DL : 0: 采用粒子群算法解决PID控制器的优化问题，是一种群体只能算法，效果不错-Particle swarm optimization algorithm
Update : 2025-02-17 Size : 1kb Publisher : ming
[matlab] pso_pid DL : 0: PID控制器的性能取决于Kp、Ki、Kd这3个参数是否合理，因此，优化PID控制器参数具有重要意义。目前，PID控制器参数主要是人工调整，这种方法不仅费时，而且不能保证获得最佳的性能。PSO已经广泛应用于函数优化、神经网络训练、模式分类、模糊系统控制以及其它应用领域，本案例将使用PSO进行PID控制器参数的优化设计。-Performance of PID controller depends on the Kp, Ki, Kd these three parameters are reasonable, therefore, to optimize PID controller parameters is important. Currently, PID controller parameters are mainly manual adjustment, this method is not only time consuming, but can not guarantee optimum performance. PSO has been widely used function optimization, neural networks, pattern classification, fuzzy systems control and other applications, in this case using the PSO is optimized PID controller parameters.
Update : 2025-02-17 Size : 1kb Publisher : 任凡