最近捣鼓ROS的时候，发现github上有人用python实现了PID，虽然可能执行效率不高，但是用python写工具的时候还是很方便的。从github上把代码搬下来，简单分析一下
给代码:
在截个都看烦了的公式意思一下吧
#!/usr/bin/python
#
# This file is part of IvPID.
# Copyright (C) 2015 Ivmech Mechatronics Ltd. <bilgi@ivmech.com>
#
# IvPID is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# IvPID is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
# title :PID.py
# description :python pid controller
# author :Caner Durmusoglu
# date :20151218
# version :0.1
# notes :
# python_version :2.7
# ==============================================================================
"""Ivmech PID Controller is simple implementation of a Proportional-Integral-Derivative (PID) Controller in the Python Programming Language.
More information about PID Controller: http://en.wikipedia.org/wiki/PID_controller
"""
import time
class PID:
"""PID Controller
"""
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):
"""Clears PID computations and coefficients"""
self.SetPoint = 0.0
self.PTerm = 0.0
self.ITerm = 0.0
self.DTerm = 0.0
self.last_error = 0.0
# Windup Guard
self.int_error = 0.0
self.windup_guard = 20.0
self.output = 0.0
def update(self, feedback_value):
"""Calculates PID value for given reference feedback
.. math::
u(t) = K_p e(t) + K_i \int_{0}^{t} e(t)dt + K_d {de}/{dt}
.. figure:: images/pid_1.png
:align: center
Test PID with Kp=1.2, Ki=1, Kd=0.001 (test_pid.py)
"""
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
self.ITerm += error * delta_time
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
# Remember last time and last error for next calculation
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):
"""Determines how aggressively the PID reacts to the current error with setting Proportional Gain"""
self.Kp = proportional_gain
def setKi(self, integral_gain):
"""Determines how aggressively the PID reacts to the current error with setting Integral Gain"""
self.Ki = integral_gain
def setKd(self, derivative_gain):
"""Determines how aggressively the PID reacts to the current error with setting Derivative Gain"""
self.Kd = derivative_gain
def setWindup(self, windup):
"""Integral windup, also known as integrator windup or reset windup,
refers to the situation in a PID feedback controller where
a large change in setpoint occurs (say a positive change)
and the integral terms accumulates a significant error
during the rise (windup), thus overshooting and continuing
to increase as this accumulated error is unwound
(offset by errors in the other direction).
The specific problem is the excess overshooting.
"""
self.windup_guard = windup
def setSampleTime(self, sample_time):
"""PID that should be updated at a regular interval.
Based on a pre-determined sampe time, the PID decides if it should compute or return immediately.
"""
self.sample_time = sample_time注释很完美，没有能解释的啊
待会写个程序，用plot画个图线，验证一下
