把上边代码实现一个参数自动调整功能

要在PID控制器中实现参数自动调整功能，通常会采用自适应控制方法。一种常见的做法是使用自校准PID (Self-Tuning PID) 或自适应PID算法，例如Proportional-Integral-Derivative with Adaptive Gain Control (PID-AGC)。这里是一个简单的示例：

import numpy as np

class AutoTuningPID:
    def __init__(self, Kp=1, Ki=0.1, Kd=0.01, adaptation_rate=0.1):
        self.Kp = Kp
        self.Ki = Ki
        self.Kd = Kd
        self.adaptation_rate = adaptation_rate
        self.error_sum = 0
        self.derivative_last = None

    def update(self, setpoint, current_value, dt):
        error = setpoint - current_value

        # Proportional term
        P_output = self.Kp * error

        # Integral term (with low-pass filter)
        if self.error_sum > 0:
            self.error_sum *= self.adaptation_rate
        self.error_sum += error * dt
        I_output = self.Ki * self.error_sum

        # Derivative term (if applicable)
        if self.derivative_last is not None:
            D_output = self.Kd * (error - self.derivative_last) / dt
        else:
            D_output = 0
        self.derivative_last = error

        # Combine and return the total output
        output = P_output + I_output + D_output

        # Update gains using adaptation rate
        self.Kp += self.adaptation_rate * (P_output - old_P_output)
        self.Ki += self.adaptation_rate * (I_output - old_I_output)

        return output, self.Kp, self.Ki, self.Kd

# 使用示例
pid = AutoTuningPID()
setpoint = 50
current_value = 45
dt = 0.1
output, Kp, Ki, Kd = pid.update(setpoint, current_value, dt)

在这个例子中，PID控制器会根据当前的输出、误差和时间步长动态调整比例(P)、积分(I)和微分(D)系数。`adaptation_rate` 控制了参数更新的速度。在实际应用中，可能还需要其他附加的安全措施和限制条件，以防止参数过于激进或不稳定。