PID算法实现

import time

class PID:

def __init__(self, P=0.2, I=0.0, D=0.0):

self.Kp = P

self.Ki = I

self.Kd = D

self.sample_time = 0.00

self.current_time = time.time()

self.last_time = self.current_time

self.clear()

def clear(self):

self.SetPoint = 0.0

self.PTerm = 0.0

self.ITerm = 0.0

self.DTerm = 0.0

self.last_error = 0.0

self.int_error = 0.0

self.windup_guard = 20.0

self.output = 0.0

def update(self, feedback_value):

error = self.SetPoint - feedback_value

self.current_time = time.time()

delta_time = self.current_time - self.last_time

delta_error = error - self.last_error

if (delta_time >= self.sample_time):

self.PTerm = self.Kp * error#比例

self.ITerm += error * delta_time#积分

if (self.ITerm < -self.windup_guard):

self.ITerm = -self.windup_guard

elif (self.ITerm > self.windup_guard):

self.ITerm = self.windup_guard

self.DTerm = 0.0

if delta_time > 0:

self.DTerm = delta_error / delta_time

self.last_time = self.current_time

self.last_error = error

self.output = self.PTerm + (self.Ki * self.ITerm) + (self.Kd * self.DTerm)

def setKp(self, proportional_gain):

self.Kp = proportional_gain

def setKi(self, integral_gain):

self.Ki = integral_gain

def setKd(self, derivative_gain):

self.Kd = derivative_gain

def setWindup(self, windup):

self.windup_guard = windup

def setSampleTime(self, sample_time):

self.sample_time = sample_time

测试PID算法

import PID

import time

import matplotlib

matplotlib.use("TkAgg")

import matplotlib.pyplot as plt

import numpy as np

from scipy.interpolate import spline

#这个程序的实质就是在前九秒保持零输出，在后面的操作中在传递函数为某某的系统中输出1

def test_pid(P = 0.2, I = 0.0, D= 0.0, L=100):

"""Self-test PID class

.. note::

...

for i in range(1, END):

pid.update(feedback)

output = pid.output

if pid.SetPoint > 0:

feedback += (output - (1/i))

if i>9:

pid.SetPoint = 1

time.sleep(0.02)

---

"""

pid = PID.PID(P, I, D)

pid.SetPoint=0.0

pid.setSampleTime(0.01)

END = L

feedback = 0

feedback_list = []

time_list = []

setpoint_list = []

for i in range(1, END):

pid.update(feedback)

output = pid.output

if pid.SetPoint > 0:

feedback +=output# (output - (1/i))控制系统的函数

if i>9:

pid.SetPoint = 1

time.sleep(0.01)

feedback_list.append(feedback)

setpoint_list.append(pid.SetPoint)

time_list.append(i)

time_sm = np.array(time_list)

time_smooth = np.linspace(time_sm.min(), time_sm.max(), 300)

feedback_smooth = spline(time_list, feedback_list, time_smooth)

plt.figure(0)

plt.plot(time_smooth, feedback_smooth)

plt.plot(time_list, setpoint_list)

plt.xlim((0, L))

plt.ylim((min(feedback_list)-0.5, max(feedback_list)+0.5))

plt.xlabel('time (s)')

plt.ylabel('PID (PV)')

plt.title('TEST PID')

plt.ylim((1-0.5, 1+0.5))

plt.grid(True)

plt.show()

if __name__ == "__main__":

test_pid(1.2, 1, 0.001, L=80)

# test_pid(0.8, L=50)

结果

以上这篇python实现PID算法及测试的例子就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。