# Source code for cpsim.controllers.PID

```
#!/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
# ==============================================================================
# add utils limit - Lin
# update DTerm using delta_pv - Lin
"""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
from .controller_base import Controller
[docs]
class PID(Controller):
"""PID Controller
"""
def __init__(self, P=0.2, I=0.0, D=0.0, current_time=None):
self.Kp = P
self.Ki = I
self.Kd = D
self.sample_time = 0.00
self.current_time = current_time if current_time is not None else time.time()
self.last_time = self.current_time
self.clear(current_time)
self.control_lo = None
self.control_up = None
[docs]
def clear(self, current_time=None):
"""Clears PID computations and coefficients"""
self.current_time = current_time if current_time is not None else time.time()
self.last_time = self.current_time
self.SetPoint = 0.0
self.PTerm = 0.0
self.ITerm = 0.0
self.DTerm = 0.0
self.last_error = 0.0
self.last_pv = None
# Windup Guard
self.int_error = 0.0
# self.windup_guard = 20.0
self.output = 0.0
[docs]
def update(self, feedback_value: float, current_time=None) -> float:
"""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 = current_time if current_time is not None else 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
delta_pv = 0
if self.last_pv:
delta_pv = feedback_value - self.last_pv
self.DTerm = 0.0
if delta_time > 0:
self.DTerm = delta_pv / delta_time
# Remember last time and last error for next calculation
self.last_time = self.current_time
self.last_error = error
self.last_pv = feedback_value
self.output = self.PTerm + (self.Ki * self.ITerm) + (self.Kd * self.DTerm)
if self.control_up is not None and self.control_up < self.output:
self.output = self.control_up
elif self.control_lo is not None and self.control_lo > self.output:
self.output = self.control_lo
return self.output
[docs]
def setKp(self, proportional_gain):
"""Determines how aggressively the PID reacts to the current error with setting Proportional Gain"""
self.Kp = proportional_gain
[docs]
def setKi(self, integral_gain):
"""Determines how aggressively the PID reacts to the current error with setting Integral Gain"""
self.Ki = integral_gain
[docs]
def setKd(self, derivative_gain):
"""Determines how aggressively the PID reacts to the current error with setting Derivative Gain"""
self.Kd = derivative_gain
[docs]
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
[docs]
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
[docs]
def set_control_limit(self, control_lo: float, control_up: float):
self.control_lo = control_lo
self.control_up = control_up
```