生命中，好多的事是这样，生活中，好多的情是这样，没有理由，也无需理由，爱就是爱，喜欢就是喜欢，没有结果，也无须结果，心甘情愿，无怨无悔。
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。
