搜索资源列表
Advanced-control-algorithm-
- 这是控制系统设计所用到几种先进的控制算法。有对传统的PID算法，和对原有PID的改进算法。其中有基于神经网络。-This is the design of control systems used in several advanced control algorithms. With the traditional PID algorithm, and improvements on the original PID algorithm. Including neural networks.
kecheng2011
- 课程设计要求 0 实验一 基于模板匹配的字符识别 1 实验二 基于C均值算法的车辆检测与跟踪 3 实验三 水果分类系统设计 5 实验四 基于遗传算法的图像歪斜校准 6 实验五 基于BP网络的函数逼近 9 实验六 空调模糊控制系统设计 -Curriculum design requires 0 Experimental one based on template matching character recognition 1 C-means algorithm
2011-12-23-1337
- 复杂网络，系统设计，牵制控制，可自行设计控制点、网络节点。内耦合矩阵，外耦合矩阵，采用全局网络，实现分析系统是否收敛。可求平衡点，Jacabi矩阵-Complex networks, systems design, contain control, can design their own control point, the network node. Coupling matrix within and outside the coupling matrix, using the globa
dfdf
- 不过MATLAB这么大型的软件那么多钱还是值得花的。 .... 网络、小波分析、信号处理、图像处理、系统辨识、控制系统设计、LMI控制、鲁棒控制- Title: Anoxic activated sludge monitoring with combined nitrate and titrimetric measurements Author(s): Petersen B Gernaey K Vanrolleghem PA Conference: 1st IWA Intern
nnpid
- 基于BP神经网络PID的对电厂气温控制系统的m文件-m files of temperature control of power plant based on Neural network PID
BP
- 一个关于人工神经网络控制实时仿真系统研究的文章-The Real Time Emulation Systemof Artificial Neural Networks Control
xy7z.ZIP
- 电液位置伺服系统的模糊神经网络控制Electro hydraulic position servo system based on fuzzy neural network control-Electro hydraulic position servo system based on fuzzy neural network control
SJWLPID
- 基于PID神经网络的倒立摆控制系统（神经网络控制）-Inverted Pendulum Control System Based on PID Neural Network
PID-BP
- 采用PID结合神经网络算法，来解决多变量控制系统的解耦控制-PID neural network algorithm to solve multi-variable control system of decoupling control
111
- 神经网络控制 徐丽娜 多变量控制系统以及辨识-Neural network control of the the Lina multi-variable control system and identification
44
- 智能控制 模糊控制 神经网络控制序号 多变量控制系统设计-Intelligent control fuzzy control of multivariable control system design of the neural network control of serial number
Multi-layer-neural-net
- 多层神经网络设计和仿真 应用与反步控制系统设计中-multi-neruo networks
Neural-Network-Design-by-Hagan
- 《神经网络设计》本书介绍了神经网络的基本结构和学习规则，重点是对这些神经网络的数学分析，训练方法和神经网络在模式识别、信号处理以及控制系统等工程实践问题中的应用-The book introduces the basic structure of the neural networks and learning rules focus on the mathematical analysis of these neural networks, training methods and neura
m2
- 神经网络控制的一些有用程序，主要有BP,RBF等算法的系统辨识和控制-Neural network control some useful procedures and system identification and control algorithms such as BP, RBF
MPIDCS
- 该代码为基于PID神经网络的系统控制算法-The code for the control algorithm of PID neural network-based system
pso
- 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 optimized control algorithm based on PID neural networkthe pso algorithm
MPIDDLX
- 该代码为带动量项的PID神经网络的系统控制算法-The code to drive the amount of items PID neural network system control algorithm
chaper3
- 《机器人控制系统设计与matlab仿真》第三章“机器人神经网络自适应控制”源代码-" Robot control system design and the matlab simulation" " robot neural network adaptive control source code
neural-network-toolbox
- 本文介绍在Matlab 环境下发电厂水位控制BP 模型的建模与仿真方法, 得出了预测模型的最优参数。仿真结果表明, MATLAB 神经网络工具箱可有效地用来解决复杂的非线性控制系统的优化设计问题。-This article describes the Matlab environment plant level control BP Model modeling and simulation methods, predictive models obtained optimal parame
mohuNNE
- 运用广义模糊神经网络辨识系统并对系统进行自适应控制仿真-NNE and self-adaptive control