C# 将入站邮件的等待延迟限制为每秒邮件数

我试图将循环（发送消息）限制为每秒特定数量的消息

\u throttle

是每秒的消息数

我的初始算法如下所示，但延迟并不平滑。
我可以做些什么改进来消除相当不平稳的延迟和突发消息。

我已经试过了滴答声和间隔最大值，但是入站计数太大了，很难补偿。在我的实现中，节气门关闭时可以达到的最大速率约为15000/秒。我正在以每秒300到1000的速率进行测试，所以我试图将速度降低很多

private class ThrottleCalculator
{
    private readonly int _throttle;
    private DateTime _lastCalculation = DateTime.Now;
    private int _count = 0;
    private int _interval = 0;

    public ThrottleCalculator(int throttle)
    {
        this._throttle = throttle;
    }

    public async Task CalculateThrottle()
    {
        this._count += 1;
        var elapsed = DateTime.Now.Subtract(this._lastCalculation).TotalMilliseconds;
        var tick = 50;
        if (elapsed > tick)
        {
            this._lastCalculation = DateTime.Now;
            int projection = this._count * (1000 / tick);
            var errorTerm = this._throttle - projection;
            this._interval = this._interval - errorTerm;
            if (this._interval < 0)
                this._interval = 0;

            // this is often several thousand, so I have to limit.
            if (this._interval > 100)
                this._interval = 100;
            await Task.Delay(this._interval);
            this._count = 0;
        }
    }
}

PID控制器算法 对于任何试图这样做的人来说，正确的方法是

比例/积分/微分控制器

我使用wiki底部的算法作为基础。 我的

kp/ki/kd

似乎可以很好地处理这里的值，保持它们的比例似乎可以产生稳定的消息流，并且延迟值非常小

private class ThrottleCalculator
{
    private readonly int _throttle;
    private DateTime _lastCalculationTime;
    private double _measured = 0;
    private double _totalError = 0;
    private double _integral = 0;
    private double _lastError = 0;

    public ThrottleCalculator(int throttle)
    {
        this._throttle = throttle;
        this._lastCalculationTime = DateTime.MinValue;
    }

    public async Task CalculateThrottle()
    {
        var kp = -.1d;      // proportional gain
        var ki = -.1d;      // integral gain
        var kd = -.1d;      // derivative gain
        var dt = 30d;       // rate of change of time. calculcations every ms;

        this._measured += 1;
        if (this._lastCalculationTime == DateTime.MinValue)
            this._lastCalculationTime = DateTime.Now;
        var elapsed = (double)DateTime.Now.Subtract(this._lastCalculationTime)
                     .TotalMilliseconds;
        if (elapsed > dt)
        {
            this._lastCalculationTime = DateTime.Now;
            var error = ((double)this._throttle / (1000d / dt)) - this._measured;
            this._totalError += error;
            var integral = this._totalError;
            var derivative = (error - this._lastError) / elapsed;
            var actual = (kp * error) + (ki * integral) + (kd * derivative);
            var output = actual;
            if (output < 1)
                output = 0;

            // i don't like this, but it seems necessary
            // so that wild wait values are never used.
            if (output > dt * 4)
                output = dt * 4;
            if (output > 0)
                await Task.Delay((int)output);
            this._measured = 0;
            this._lastError = error;
        }
    }
}

---

我不知道你想实现什么，但好吧。使用控制回路进行节流是聪明的！要匹配常规PID方程，可能需要将积分项乘以经过的时间。

private class ThrottleCalculator
{
    private readonly int _throttle;
    private DateTime _lastCalculationTime;
    private double _measured = 0;
    private double _totalError = 0;
    private double _integral = 0;
    private double _lastError = 0;

    public ThrottleCalculator(int throttle)
    {
        this._throttle = throttle;
        this._lastCalculationTime = DateTime.MinValue;
    }

    public async Task CalculateThrottle()
    {
        var kp = -.1d;      // proportional gain
        var ki = -.1d;      // integral gain
        var kd = -.1d;      // derivative gain
        var dt = 30d;       // rate of change of time. calculcations every ms;

        this._measured += 1;
        if (this._lastCalculationTime == DateTime.MinValue)
            this._lastCalculationTime = DateTime.Now;
        var elapsed = (double)DateTime.Now.Subtract(this._lastCalculationTime)
                     .TotalMilliseconds;
        if (elapsed > dt)
        {
            this._lastCalculationTime = DateTime.Now;
            var error = ((double)this._throttle / (1000d / dt)) - this._measured;
            this._totalError += error;
            var integral = this._totalError;
            var derivative = (error - this._lastError) / elapsed;
            var actual = (kp * error) + (ki * integral) + (kd * derivative);
            var output = actual;
            if (output < 1)
                output = 0;

            // i don't like this, but it seems necessary
            // so that wild wait values are never used.
            if (output > dt * 4)
                output = dt * 4;
            if (output > 0)
                await Task.Delay((int)output);
            this._measured = 0;
            this._lastError = error;
        }
    }
}

Actual: 19.2000 Output: 19.2000 Integral:   -209 Derivative:      .0000 Error:   17
Actual: 17.5000 Output: 17.5000 Integral:   -192 Derivative:      .0000 Error:   17
Actual: 15.8000 Output: 15.8000 Integral:   -175 Derivative:      .0000 Error:   17
Actual: 33.8104 Output: 33.8104 Integral:   -255 Derivative:    -3.1040 Error:  -80
Actual: 21.8931 Output: 21.8931 Integral:   -238 Derivative:     2.0686 Error:   17
Actual: 20.4000 Output: 20.4000 Integral:   -221 Derivative:      .0000 Error:   17
Actual: 18.7000 Output: 18.7000 Integral:   -204 Derivative:      .0000 Error:   17
Actual: 17.0000 Output: 17.0000 Integral:   -187 Derivative:      .0000 Error:   17
Actual: 15.3000 Output: 15.3000 Integral:   -170 Derivative:      .0000 Error:   17
Actual: 31.0752 Output: 31.0752 Integral:   -239 Derivative:    -2.7520 Error:  -69