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我正在尝试将循环（正在发送消息）限制为每秒特定数量的消息。_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。
我可以做哪些改进来消除相当颠簸的延迟和消息突发。

我玩过滴答声和最大间隔，但入站计数如此之大，难以弥补。在我的实现中关闭油门可以达到的最大速率约为 15000/秒。我正在测试每秒 300 到 1000 之间的速率，所以我试图减慢它的速度。

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;
        }
    }
}

使用它的代码每次迭代都会调用它。

var throttle = new ThrottleCalculator(600); // 600/s
while (message = getMessage())
{
    ... // do stuff with message.
    if (throttle != null)
       await throttle.CalculateThrottle();
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1 回答 1

3

PID 控制器算法

对于其他尝试此操作的人，正确的方法是PID 控制器算法。
Proportional / Integral / Derivative Controller

我使用了 wiki 底部的算法作为基础。我kp / ki / kd似乎与这里的值配合得很好，保持它们的比例似乎会产生一个很好的稳定消息流，以及非常严格的延迟值。

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;
        }
    }
}

我的价值观是这样的：

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
于 2016-07-15T09:47:41.877 回答