[time-nuts] PLL Math Question
magnus at rubidium.dyndns.org
Fri Mar 14 12:20:16 EDT 2014
On 13/03/14 13:57, Jim Lux wrote:
> On 3/12/14 10:06 PM, Chris Albertson wrote:
>> On Wed, Mar 12, 2014 at 9:13 PM, Daniel Mendes <dmendesf at gmail.com>
>>> This is a FIR x IIR question...
>>> moving average = FIR filter with all N coeficients equalling 1/N
>>> exponential average = using a simple rule to make an IIR filter
>> Isn't his "moving average" just a convolution of the data with a box car
>> function? That treats the last N samples equally and is likely not
>> optimal. I think why he wants is a low pass filter.
> A moving average (or rectangular impulse response) *is* a low pass
> filter. The frequency response is of the general sin(x)/x sort of
> shape, and it has deep nulls, which can be convenient (imagine a moving
> average covering 1/60th of a second, in the US.. it would have strong
> nulls at the line frequency and harmonics)
> This method is like
>> the hockey player who skates to where to puck was about 5 seconds
>> ago. It
>> is not the best way to play the game. He will in fact NEVER get to the
>> puck if the puck is moving he is domed to chase it forever.. Same here
>> you will never get there.
> That distinction is different than the filter IIR vs FIR thing. Filters
> are causal, and the output always lags the input in time. if you want
> to predict where you're going to be you need a different kind of model
> or system design. Something like a predictor corrector, for instance.
>> But if you have a long time constant on the control loop you have in
>> the kind of "averaging" you want, one that tosses out erratic noisy data.
>> A PID controller uses only three memory locations and is likely the best
> PID is popular, having been copiously analyzed and used over the past
> century. It's also easy to implement in analog circuitry.
> ANd, there's long experience in how to empirically adjust the gain
> knobs, for some kinds of controlled plant.
> However, I don't know that the simplicity justifies its use in modern
> digital implementations: very, very few applications are so processor or
> gate limited that they couldn't use something with better performance.
> If you are controlling a physical system with dynamics that are well
> suited to a PID (e.g. a motor speed control) then yes, it's the way to
> go. But if PIDs were so wonderful, then there wouldn't be all sorts of
> "auto-tuning" PIDs out there (which basically complexify things by
> trying to estimate the actual plant model function, and then optimize
> the P,I, and D coefficients).
> PID controllers don't do well when there's a priori side knowledge
> available. For instance, imagine a thermostat kind of application where
> you are controlling the temperature of an object outside in the sun. You
> could try to control the temperature solely by measuring the temp of the
> thing controlled, and comparing it against the setpoint (a classic PID
> sort of single variable loop). Odds are, however, that if you had
> information about the outside air temperature and solar loading, you
> could hold the temperature a lot more tightly and smoothly, because you
> could use the side information (temp and sun) to anticipate the
> heating/cooling demands.
> This is particularly the case where the controlled thing has long time
> lags, but low inertia/mass.
Extending a PI or PID loop to incorporate aiding signals isn't hard. In
fact that's what happens in GPS receivers. Properly done aiding signals
will reduce the phase errors to do loop stress and allow for even
Each GPS channel in a receiver contains a carrier and a code loop. The
carrier loop aids the code loop in frequency tracking. It is also common
to have both a frequency and phase detector and then aid the normal
phase-driven PI loop with a frequency detector hint.
A nice aspect about frequency aiding is that it has a strong pull-in
property when the input signal and loop is far away, and that's when the
phase-lock-in is very weak. As the pull-in progresses, the frequency
aiding gets weaker while the phase locked becomes stronger, as the
Bessel polynom gets higher for the beat frequency. Eventually the
phase-locking takes over in strength and the frequency aiding
essentially dismisses itself. This is a great example of how a classical
loop can be extended without getting into very esoteric systems.
>> We have to define "best". I'd define it as "the error integrated over
>> is minimum". I think PiD gets you that and it is also easy to program
>> uses very little memory. Just three values (1) the error, (2) the
>> total of
>> all errors you've seen (in a perfect world this is zero because the
>> positive and negative errors cancel) and (3) the rate of change in the
>> error (is it getting bigger of smaller and how quickly?) Multiply
>> each of
>> those numbers by a constant and that is the correction to the output
>> It's maybe 6 or 10 lines of C code. The "magic" is finding the
>> values for the constants.
> And that magic is sometimes a lot of work.
> And practical PID applications also need things like integrator reset to
> prevent wind-up issues, and clamps, or variable gains.
> PID, or PI, is, as you say, easy to code, and often a good first start,
> if you have a system with fast response, and lots of gain to work with.
> It's like building circuits with an opamp: big gain bandwidth product
> makes it more like an ideal amplifier where the feedback components
> completely determine the circuit behavior. Put in hysteresis, or a time
> delay, and things start to not look so wonderful.
There is a limit to how high the bandwidth-delay product can be for a
certain damping. This is covered in literature and I actually used one
of those articles in an article I wrote. Adding deep moving averagers
behaves like a delay, so there is a limit on how long moving averager
you can have in your loop before it destabilizes that loop.
I would guestimate that the effective delay of a moving average is half
it's length, and the product it has with the bandwidth of the loop may
not be too high, which means that there is a practical limit to how
"deep" it can filter. The exponential average filter has a practical
limit too, which is kind of similar and a fairly simple rule of thumb
makes sure it doesn't move the dominant pole-pair too much. On the other
hand, following that rule of thumb, you can have multiple filters or for
that matter higher grade filters without too much interference to how
dimensioning is done and stability is maintained.
There is also the higher integration variants.
The traditional PI/PID loop allows for a whole variant of extensions if
you just play around a little.
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