PID演算法實現

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#積分
            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

 

測試PID演算法

import PID
import time
import matplotlib
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
#這個程式的實質就是在前九秒保持零輸出，在後面的操作中在傳遞函式為某某的系統中輸出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))控制系統的函式
        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)
 

結果