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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)。
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Size: 1666 |
Author: dake |
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Description: PID calculations for the _pid structure *a. This function uses the positional form of the pid equation, and incorporates an integral windup prevention algorithim. Rectangular integration is used, so this function must be repeated on a consistent time basis for accurate control. -PID calculations for the _pid structure*a. This function uses the positional form of the pid equation, and incorporates an integral windup prevention algorithim. Rectangular integration is used, so this function must be repeated on a consistent time basis for accurate control.
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Size: 2048 |
Author: 任 |
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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: ARMA模型建立程序,给出自相关序列,指定ARMA模型的P阶,Q阶参数,得出相应的参数值
function [bq ,ap]=armahat(rx,p,q)-ARMA model for the establishment of procedures, to come from related sequences, designated the P-order ARMA model, Q-order parameters, the corresponding parameter values derived function [bq, ap] = armahat (rx, p, q)
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Size: 1024 |
Author: 赵慧羲 |
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Description: 遗传算法的PID调节
题目:已知 ,利用GA 寻优PID参数,其中K=1,T=2, ,二进制/实数编码,位数不限,M,Pc,Pm自选,性能指标 ,Q=100为仿真计算步长。-PID regulation of genetic algorithms Title: known, the use of PID parameters of GA optimization, in which K = 1, T = 2,, binary/real-coded, not limited to the median, M, Pc, Pm-on-demand, performance indicators, Q = 100 step for the simulation.
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Size: 2048 |
Author: qiqi |
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Description: 三篇关于MATLAB,模糊PID控制,液位控制与仿真的文章-3 on MATLAB, Fuzzy PID control, level control and simulation of the article
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Size: 211968 |
Author: 410106925 |
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Description: TMS28335初始化完成之后,
1、 先DDS产生73.35hz的方波。(问流量管固定频率)
2、 乘法器的另一个数字端输入乘数直接给一个固定值(按照5v),系数是固定的就是对应PID输出的那个接口,串行十二位信号输出(需要先定好一个GPIO接口)。
3、 再延迟一定的时间0.1s或其他时间之后,开始ad采集信号,分别采两路AD信号,此时不稳定(为什么要等到一定的幅值才开始采集AD信号)
4、 选择250点估计一个频率,频率估计的方法采用计算峰值次数的方法或者过零点,总之是为了保证精度采用时域估计的算法,这一块主要是一个扫频子程序,计算频率共振点。
5、 之后改变DDS的输出频率,循环对512点的数据进行扫频的处理
6、 频率控制完成之后,就可以缓慢降低PID控制输出的参数,此时暂时不计算频率,通过不断调整系数使AB的幅度保持在1 的范围内。
7、 测试幅度控制稳定之后a、采用幅度和频率同时控制b。采集数据进入频率估计和相位差估计的后续程序的大循环
8、 注意:采样和控制是同时进行的,所以要设置中断,以及看懂AD的程序,以及内部存储以及数据处理资源的分配。
-TMS28335 initialization is complete,
1, the first DDS generated square wave of 73.35hz. (Q flow tube fixed frequency)
2, another digital side of the multiplier input multiplier directly to a fixed value (in accordance with 5v), the coefficient is fixed corresponding PID output interface, serial twelve signal output (need to be a good one GPIO interface).
3, and then after a certain time delay 0.1s or other time, ad signal acquisition were collected two AD signal instability (Why wait until a certain amplitude began collecting AD signal)
4, 250 point estimate a frequency, frequency estimation method using the method of calculation of the number of peak or zero crossing, in short, in order to ensure the accuracy of time-domain estimation algorithm, this piece is a sweep subroutine to calculate the frequency resonance point.
5, after the change of the output frequency of the DDS data of 512 points, the loop processing Sweep
6, after the completion of the frequency control, it can sl
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Size: 164864 |
Author: kiss |
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Description: PID: LDP #DP_B01 数据页4——0200h~0280h
SETC SXM 允许符号扩展
LACL VREF Vref,Q.15*256
SUB V V,Q.15*256
SACL VE2 e(k)= Vref-V,Q15*256
SUB VE1 e(k-1),Q15*256
SACL PIDTMP1 Delta(e(k))=e(k)-e(k-1),Q15/256
SUB VE1
ADD VE0 e(k-2),Q15*256
SACL PIDTMP3 Delta(e(k)) -Delta(e(k-1))= e(k)-2e(k-1)+e(k-2)
Q15*256
LT KP Kp,Q15*32
MPY PIDTMP1
PAC-PID: LDP #DP_B01 数据页4——0200h~0280h
SETC SXM 允许符号扩展
LACL VREF Vref,Q.15*256
SUB V V,Q.15*256
SACL VE2 e(k)= Vref-V,Q15*256
SUB VE1 e(k-1),Q15*256
SACL PIDTMP1 Delta(e(k))=e(k)-e(k-1),Q15/256
SUB VE1
ADD VE0 e(k-2),Q15*256
SACL PIDTMP3 Delta(e(k)) -Delta(e(k-1))= e(k)-2e(k-1)+e(k-2)
Q15*256
LT KP Kp,Q15*32
MPY PIDTMP1
PAC
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Size: 6032384 |
Author: liangguocai |
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Description: DSP 的数字控制设计方面的较好的技术资料,包括Q格式含义,Q格式确定等方面的说明。-DSP digital control better technical design information, including the description of the meaning of Q format, Q format determination and so on.
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Size: 1034240 |
Author: lvhongtao |
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Description: q saco filho da puta do racaralho porra librera essa perda chist
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Size: 6670336 |
Author: tkm123 |
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