关于追小球的pid算法中 _RC 这个参数是什么？

veb1

from pyb import millis
from math import pi, isnan

class PID:
_kp = _ki = _kd = _integrator = _imax = 0
_last_error = _last_derivative = _last_t = 0
_RC = 1/(2 * pi * 20)
def init(self, p=0, i=0, d=0, imax=0):
self._kp = float(p)
self._ki = float(i)
self._kd = float(d)
self._imax = abs(imax)
self._last_derivative = float('nan')

def get_pid(self, error, scaler):
    tnow = millis()
    dt = tnow - self._last_t
    output = 0
    if self._last_t == 0 or dt > 1000:
        dt = 0
        self.reset_I()
    self._last_t = tnow
    delta_time = float(dt) / float(1000)
    output += error * self._kp
    if abs(self._kd) > 0 and dt > 0:
        if isnan(self._last_derivative):
            derivative = 0
            self._last_derivative = 0
        else:
            derivative = (error - self._last_error) / delta_time
        derivative = self._last_derivative + \
                                 ((delta_time / (self._RC + delta_time)) * \
                                    (derivative - self._last_derivative))
        self._last_error = error
        self._last_derivative = derivative
        output += self._kd * derivative
    output *= scaler
    if abs(self._ki) > 0 and dt > 0:
        self._integrator += (error * self._ki) * scaler * delta_time
        if self._integrator < -self._imax: self._integrator = -self._imax
        elif self._integrator > self._imax: self._integrator = self._imax
        output += self._integrator
    return output
def reset_I(self):
    self._integrator = 0
    self._last_derivative = float('nan')

kidswong999

我也不知道是什么，这个代码是我从网上抄的。

cghq

补问一句，imax是啥？总让我想起电影。。

veb1

@cghq imax是积分项设置的一个最大值，积分离散化就是累加，为了消除累加效应设置了个最大值

veb1

@kidswong999 这个参数只在微分项里出现，可是小车这个是pi控制，没有用到程序里的微分项d，您看看式中这个 dt/(RC + dt)是表达什么，这个RC跟Td（微分时间常量）和kd有关系吗？看得懵懵的哈哈

cghq

@veb1 谢谢