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Description: nn modelling and auto-pid controller
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Size: 13999 |
Author: fling |
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Description: 基于神经网络的PID控制不是用神经网络来整定PID的参数，而是用神经网络直接作为控制器，通过训练神经网络的权系数间接地调整PID参数。-based on neural network PID control is not using neural networks to PID parameters, Rather, as a neural network controller directly, through the training of the neural network weights indirectly PID parameters to adjust.
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Size: 69632 |
Author: 戚伟 |
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Description: 遗传bp神经网络在pid控制器中的应用,多多指教-genetic bp pid neural network controller in the application of the exhibitions! !
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Size: 84992 |
Author: angel |
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Description: 基于BP神经网络的 参数自学习控制
（1）确定BP网络的结构，即确定输入层节点数M和隐含层节点数Q，并给出各层加权系数的初值 和 ，选定学习速率 和惯性系数 ，此时k=1；
（2）采样得到rin(k)和yout(k)，计算该时刻误差error(k)=rin(k)-yout(k)；
（3）计算神经网络NN各层神经元的输入、输出，NN输出层的输出即为PID控制器的三个可调参数 ， ， ；
（4）根据(3.34)计算PID控制器的输出u(k)；
（5）进行神经网络学习，在线调整加权系数 和 ，实现PID控制参数的自适应调整；
（6）置k=k+1，返回（1）。
-Based on the parameters of BP neural network self-learning control (1) to determine the structure of BP network, that is, determine the input layer nodes M and hidden layer nodes Q, and gives all levels of the initial value and the weighted coefficient, the selected learning rate and inertia coefficient, when k = 1 (2) sample has been rin (k) and the yout (k), calculate the moment of error error (k) = rin (k)-yout (k) (3) calculation of neural network NN all floors of the neurons in input and output, NN output layer is the output of PID controller for the three adjustable parameters,, (4) According to (3.34) Calculation of PID controller output u (k) (5) to carry out neural network learning, on-line adjustment of the weighted coefficient and, realize the adaptive PID control parameters adjust (6) purchase k = k+ 1, return (1).
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Size: 1024 |
Author: dake |
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Description: nn modelling and auto-pid controller
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Size: 14336 |
Author: fling |
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Description: 摘要：给出了解决机器人控制问题一种神经网络方法。使用一个分级神经网络(NN)结构学习刚体机器人动力学特点。对于一般类别的机械手，使用前训练一系列的三层前馈网络模块，然后把这些基函数实时地用于第四层。使用线性控制原理，辅以非线性补偿控制机械手，使学得的机械手动力学知识创建一个在整个工程中高速控制机械手的控制器。模拟结果表明控制器的性能得到了大大提高。-Abstract: This paper presents a solution to the issue of robot control neural network method. Using a hierarchical neural network (NN) structure to study the characteristics of rigid robot dynamics. For the general category of the mechanical hand, the use of a series of three training feedforward network module, and then these basis functions in real time for the fourth floor. The use of linear control theory, supplemented by non-linear compensation control robot to learn the robot dynamics knowledge to create a project in the entire high-speed control manipulator controller. Simulation results show that the controller performance has been greatly enhanced.
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Size: 40960 |
Author: 范卫华 |
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Description: 采用S函数写的多变量单神经元PID控制的SIMULINK仿真-NN PID CONTROLLER WRITED BY S FUNCTION
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Size: 1024 |
Author: 李林 |
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Description: 本控制器采用CMAC前馈控制，CMAC采用有导师的学习算法-a controller based CMAC nn
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Size: 1024 |
Author: 李林 |
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Description: code for pid controller using bpn -code for pid controller using bpn nn
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Size: 1024 |
Author: Ashish Panpalia |
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Description: NN CONTROLLER FOR UPQC
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Size: 4404224 |
Author: ravikumar |
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Description: To improve efficiency, PV system must operate on maximum power point (MPP) so necessary to determine it.
Thus, when a direct connection is carried out between the source and the load, the output of the PV module is seldom maximum value and the operating point is not optimal.
To overcome this problem, it is necessary to add an adaptation device, an MPPT controller with a DC/DC converter between the source and the load, Fig. 8 [8].
The characteristics of a PV system vary with temperature and irradiance, Fig. 3, 4, 5, 6. Therefore, an MPPT controller is also required to track the new modified maximum power point in its corresponding curve to arrange PV system operate at peak power point so that maximum power can be delivered to load. Whenever, a variation in temperature and/or irradiance occurs.
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Size: 1260544 |
Author: Ayat |
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Description: 基于MATLAB编写的基于遗传算法的RBF-NN训练程序-Based on the PID controller based on genetic algorithm RBF-NN MATLAB_SIMULINK prepared
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Size: 4096 |
Author: 王强 |
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Description: adaptive nonlinear controller Synthesis and Flight Test Evaluation On an Unmanned Helicopter
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Size: 15360 |
Author: pari |
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Description: 基于BP神经网络的PID控制器结构,控制器由两部分组成：一是常规PID控制器，用以直接对对象进行闭环控制，且3个参数在线整定；二是神经网络NN，根据系统的运行状态，学习调整权系数，从而调整PID参数，达到某种性能指标的最优化。-基于BP神经网络的PID控制器结构,控制器由两部分组成：一是常规PID控制器，用以直接对PID controller structure BP neural network, the controller consists of two parts: First, a conventional PID controller for closed loop control of the direct object, and three-line parameter tuning the second is the neural network NN, operate in accordance with the system state, learning to adjust the weights to adjust the PID parameters to achieve certain performance optimization.
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Size: 2048 |
Author: 马腾 |
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