Description: 有脉冲干扰 下的柔性机械臂的模糊控制方法。采用神经网络训练出来的T—S模糊控制器，控制效果不错。只有仿真模块，没有文字说明。-pulse interference with the interference of fuzzy manipulator control methods. Using neural network training, the T-S fuzzy controller, control effectiveness. Only Simulation Module, there is no written statement. Platform: |
Size: 7168 |
Author:郑军 |
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Description: 将基于聚类分析的神经网络-模糊控制器应用于火电厂锅炉控制系统的访问研究-Cluster analysis will be based on neural network- fuzzy controller used in thermal power plant boiler control system access to research Platform: |
Size: 3208192 |
Author:陆见 |
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Description: 一种基于模糊神经网络的控制策略，融合了模糊控制和神经网络的优点，根据变量的动态调整实施控制器的动态参数调整-Based on fuzzy neural network control strategy, the convergence of fuzzy control and neural network advantages, in accordance with the dynamic adjustment of the implementation of variable controller to adjust the dynamic parameters Platform: |
Size: 232448 |
Author:周炜 |
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Description: 用BP神经网络实现模糊控制规则为T=int[(e
+ec)/2]的模糊神经网络控制器。可以改变隐层节点数和学习速率。网络训练算法是变学习速率法。-BP neural network with fuzzy control rules for the T = int [(e+ Ec)/2] of the fuzzy neural network controller. Can change the hidden layer nodes and learning rate. Network training algorithm is a variable learning rate method. Platform: |
Size: 4096 |
Author:韩梅 |
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Description: 为了提高三级倒立摆系统控制的响应速度和稳定性,在设计Mamdani 型模糊推理规则控制器控制倒立摆系统稳定的基础上,
设计了一种更有效率的基于Sugeno 型模糊推理规则的模糊神经网络控制器。该控制器使用BP 神经网络和最小二乘法的混
合算法进行参数训练,能够准确归纳输入输出量的模糊隶属度函数和模糊逻辑规则。通过与Mamdani 型控制器的仿真对比,
表明该Sugeno 型模糊神经网络控制器对三级倒立摆系统的控制具有良好的稳定性和快速性,以及较高的控制精度。-In order to improve the three-level control of inverted pendulum system response speed and stability, in the design of Mamdani-type fuzzy inference rules of the system controller to control the stability of inverted pendulum on the basis of a more efficient design based on Sugeno-type fuzzy inference rules of fuzzy neural network controller. The controller is the use of BP neural network and hybrid least squares training algorithm parameters can be accurately summed up the amount of input and output fuzzy membership function and fuzzy logic rules. Mamdani-type controller with a simulation comparison shows that the Sugeno-type fuzzy neural network controller for the three-tier control of inverted pendulum system with good stability and fast, as well as a higher control precision. Platform: |
Size: 551936 |
Author:月到风来AA |
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Description: < 控制系统计算机辅助设计--MATLAB语言与应用>>系统地介绍了国际控制界最流行的控制系统计算机辅助设计语言MATLAB，侧重于介绍MATLAB语言编程基础与技巧、数学问题的MATLAB求解、线性系统计算机辅助分析、控制系统与其他复杂系统的Simulink建模，控制系统的计算机辅助设计方法，包括串联控制器、状态反馈控制器、多变量系统频域设计、PID控制器设计、最优控制器设计、LQG/LTR控制器设计、H2=H1 最优控制、分数阶控制、自适应控制、模糊控制、神经网络控制、遗传算法优化控制等。本电子文档为其源码光盘内容，源码多多，利于学习参考。-"" Control System for Computer-Aided Design- MATLAB language and application of "" a systematic introduction to the international control of world s most popular computer-aided control system design language MATLAB, introduced the MATLAB language programming focusing on the foundation and skills, the MATLAB mathematical problem solving, computer-aided analysis of linear systems, control systems and other complex systems Simulink modeling, control system, computer-aided design methods, including serial controller, state feedback controller, multi-variable system, frequency-domain design, PID controller design, optimal controller design, LQG/LTR controller design, H2 = H1 optimal control, fractional order control, adaptive control, fuzzy control, neural network control, genetic algorithm to optimize control. This electronic document its source code CD-ROM content, source code lot, conducive to learning for reference. Platform: |
Size: 2137088 |
Author:任勇 |
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Description: These set of programs are written to design a robust power system stabilizer for minimizing the effects of low frequency oscillations in electric power systems. A complete nonlinear model of the power system represented by a single machine connected to an infinite bus is developed in the Simulink environment. A fuzzy Power System Stabilizer is designed using the fuzzy logic toolbox of matlab and its parameters are tuned by a NEural Network controller. Platform: |
Size: 15360 |
Author:al-amin |
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Description: 不用到matlab工具箱，进行神经网络控制器设计，采用BP方法-Do not have to matlab toolbox, the neural network controller design, using BP method Platform: |
Size: 1024 |
Author:海朝 |
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Description: 摘要：为了减少先验知识对统一潮流控制器中模糊规则的设计和电力系统参数的变化对统一潮流控制器性能的影响， 文中采用模糊神经网络来设计统一潮流控制器-Abstract: In order to reduce a priori knowledge of the unified power flow controller in the fuzzy rules in the design and power system parameters on the unified power flow controller performance, the paper design of fuzzy neural networks to a unified power flow controller Platform: |
Size: 256000 |
Author:唐传胜 |
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Description: ：针对能够采用仿射非线性表示的含有未建模动态的SISO非线性系统，讨论了一种基于神经网络的自适应
控制方法．该方法对受控对象的已知部分．采用反馈线性化方法设计控制器，用神经网络在线补偿未建模动态及
外部干扰等引起的误差，从而实现自适应控制。对具有未建模动态的双车倒立摆设计了输出反馈自适应控制系
统．仿真表明该方法是有效的。 -A discussion is devoted to design neural network adaptive control scheme of the SISO (single
input and single output)nonlinear system with unmodeled dynamics．According to the known part of
the plant．feedback Iinearization method iS used to design the controller．The error resulted from the un～
modeled dynamics and the external disturbance is compensated by online neural network．The neural
networks are designed as a five layer fuzzy neural network and its construction is optimized by genetic al—
gorithms．It has been used to approtimate the nonlinear function of system and to compesate the error of
unmodeled dynamic．The design of neural network adaptive controller has better performances．The
method is verified by the digital simulation of tWO—·cart with inverted·-pendulum system and unmodeled
dynamics． Platform: |
Size: 163840 |
Author: |
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Description: In this paper a Conventional PD Controller and Fuzzy Neural Controller for trajectory tracking of mobile robot
platform is presented. Using computed torque method is given input- torque on mobile robot wheels. The
locomotion control structure is based on integration of kinematics and dynamics model of mobile robot base.
The proposed Control scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on wheeled mobile robot. Fuzzy Neural Network-Rule base, is optimized using
Genetic Algorithm. Simulations are done using Matlab software.
Key words:Mobile Robot, Conventional, Fuzzy Logic, Neural Network, Genetic Algorithm, trajectory tracking,-In this paper a Conventional PD Controller and Fuzzy Neural Controller for trajectory tracking of mobile robot
platform is presented. Using computed torque method is given input- torque on mobile robot wheels. The
locomotion control structure is based on integration of kinematics and dynamics model of mobile robot base.
The proposed Control scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on wheeled mobile robot. Fuzzy Neural Network-Rule base, is optimized using
Genetic Algorithm. Simulations are done using Matlab software.
Key words:Mobile Robot, Conventional, Fuzzy Logic, Neural Network, Genetic Algorithm, trajectory tracking, Platform: |
Size: 296960 |
Author:jacobjacobjacob17 |
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