Description: 用神经网络来控制一阶倒立摆，给出matlab的simulink仿真-neural network to control a band inverted pendulum, is Matlab Simulink simulation Platform: |
Size: 8930 |
Author:张得 |
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Description: 用神经网络来控制一阶倒立摆，给出matlab的simulink仿真-neural network to control a band inverted pendulum, is Matlab Simulink simulation Platform: |
Size: 8192 |
Author:张得 |
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Description: 倒立摆matlab程序设计与实现
倒立摆matlab程序设计与实现-inverted pendulum Matlab Program Design and Implementation of an inverted pendulum Matlab Program Design and Implementation Platform: |
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Author:郭振兴 |
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Description: 用RBF神经网络和模糊控制方法控制二级倒立摆源码-Using RBF neural networks and fuzzy control method to control a double inverted pendulum source Platform: |
Size: 52224 |
Author:王启源 |
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Description: 自己编制的倒立摆matlab7的程序，采用神经网络控制方法-Prepared their own inverted pendulum matlab7 procedures, the use of neural network control method Platform: |
Size: 44032 |
Author:王强 |
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Description: 本文档包括一级,二级,三级倒立摆的设计过程,有了这个神经网络的大作业就好应付了-This document, including at the primary, secondary and tertiary design process inverted pendulum, with the neural network to cope with large operations like the Platform: |
Size: 203776 |
Author:清华 |
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Description: 一级倒立摆的模糊控制与神经网络控制。Simulink仿真环境。使用说明：在使用模糊控制时先把*.fis导入workspace，否则无法运行。-An inverted pendulum fuzzy control and neural network control. Simulink simulation environment. Usage: in the use of fuzzy control to import*. fis first workspace, otherwise it is impossible to run. Platform: |
Size: 20480 |
Author:时光 |
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Description: 倒立摆是一种复杂、时变、非线性、强耦合、自然不稳定的高阶系统，许多抽象的控制理论概念都可以通过倒立摆实验直观的表现出来。基于人工神经网络BP算法的倒立摆小车实验仿真训练模型，其倒立摆BP网络为4输入3层结构。输入层分别为小车的位移和速度、摆杆偏离铅垂线的角度和角速度。隐含层单元数16个。输出层设置为1个输出单元。输入层采用Tansig函数，隐含层采用Logsig函数，输出层采用Purelin函数。用Matlab 6.5数值计算软件对模型进行学习训练，并与线性反馈控制逻辑算法对比，表明倒立摆控制BP算法精度高、收敛快，在非线性控制、鲁棒控制等领域具有良好的应用前景。 -Inverted pendulum is a complex, time-varying, nonlinear, strong coupling, the natural instability of the high-end systems, many of the abstract concept of control theory to pass through the inverted pendulum experiment demonstrated intuitive. Based on artificial neural network BP algorithm inverted pendulum experiment simulation training model car, the Inverted Pendulum BP network input 3-layer structure of 4. Input layer, respectively, for the car s displacement and speed of deviation from the plumb line placed under the angle and angular velocity. Hidden layer unit number 16. Output layer is set to an output unit. Tansig function using input layer, hidden layer Logsig function used, the output layer Purelin function. Numerical calculation using Matlab 6.5 software for learning and training model, and linear feedback control logic algorithm comparison, show that the inverted pendulum control of BP algorithm and high precision, fast convergence in nonlinear control, robust control and Platform: |
Size: 217088 |
Author:月到风来AA |
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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: 经典倒立摆问题的神经网路控制器仿真，对了解神经控制和simulink仿真很有用-Classic inverted pendulum control problem of neural network simulation, neural control and the understanding of the usefulness of simulation simulink Platform: |
Size: 11264 |
Author:Charly |
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Description: 倒立摆的仿真程序，作为模糊神经网络的入门程序很不错。-Inverted pendulum simulink simulation program as a fuzzy neural network entry procedure very well Platform: |
Size: 7168 |
Author:artemis |
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Description: This paper gives idea about Multiple-Model Control of pH Neutralization Plant
Using the SOM Neural Networks Platform: |
Size: 162816 |
Author:sen |
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Description: 基于BP神经网络的二级倒立摆控制器选择小车的位移和速度及两个摆杆偏离铅锤线的角度和角速度为输入数据。并经训练可得到一个神经网络控制器。-The controller of the double inverted pendulum based on the BP neural network chooses displacement and speed of the car, the angle between the two pendulums bar and vertical line and angle speed as the input date. A BP network controller can then be got by training. Platform: |
Size: 1386496 |
Author:durongmao |
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Description: 基于遗传算法和BP神经网络控制倒立摆的程序，用遗传算法优化神经网络权值阈值以达到更好的控制效果-Based on genetic algorithm and BP neural network control procedures for the inverted pendulum, with a genetic algorithm neural network weight threshold in order to achieve better control performance Platform: |
Size: 37888 |
Author:李增光 |
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Description: 学校布置的神经网络控制的大作业，控制三级倒立摆的，实验效果非常好！-School layout neural network control of a large operation, control triple inverted pendulum, the experimental results is very good! Platform: |
Size: 203776 |
Author:风云 |
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Description: 利用RBF神经网络对倒立摆系统进行控制，仿真证明能够对倒立摆的位置和速度进行很好的跟踪-By using RBF neural network to control the inverted pendulum system, the simulation prove that the position and speed of the inverted pendulum can be a good tracking Platform: |
Size: 12288 |
Author:小布 |
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Description: 利用强化学习的自适应动态规划中的值迭代和策略迭代方法，神经网络控制方法，LQR状态调节器最优控制方法，实现了三维倒立摆在飞行器上的稳定控制。鲁棒性很强，进行了高斯白噪声的扰动实验。-Reinforcement learning adaptive dynamic programming in value iteration and policy iteration method, neural network control method, LQR state regulator optimal control method to achieve a three-dimensional inverted pendulum on the vehicle stability control. Very robust, conducted experiments Gaussian white noise disturbance. Platform: |
Size: 50176 |
Author:边疆 |
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