smoothing pot input

This seems to work, but is very slow to respond. How can I speed up the response?

float smooth ;


void loop() 
{
SSerial.print(analogRead(5));  //show raw output of pot value
SSerial.print(" ");                  // add a space for readibility

smooth = 0.9 * smooth + 0.1 * analogRead(5);  
SSerial_println(smooth);  //show filtered output of pot value

delay (100);
}

Take the delay() out?

db2db:
This seems to work, but is very slow to respond. How can I speed up the response?

First, let's review snippets from some of the replies...

That code uses an uninitialized variable

missing the proper initialization

And it is only the initialization of the variable that is missing

I can't help but notice that the code you posted does not initialize smooth. Do you think that might be the problem?

smooth is initialised to zero by the compiler, so it is going to take a while to ramp up.

AWOL:
smooth is initialised to zero by the compiler, so it is going to take a while to ramp up.

No, its not. Only static variables are initialized by the compiler. Non-statics will have a random value.

My question is, what is a reasonable value to initialize with?

No, its not. Only static variables are initialized by the compiler. Non-statics will have a random value.

It's a global; it is initialised to zero.
Happily, the float representation of zero is the same as int or long.

My question is, what is a reasonable value to initialize with?

A reading from your pot. Do it in setup().

skyjumper:
My question is, what is a reasonable value to initialize with?

  1. Average of N samples where N is about the same history you get from the EWMA (for ? = 0.9, N = 4 is adequate).

  2. Start at zero and toss out values until the EWMA has a complete history (for ? = 0.9 the first six values are be discarded).

  3. Or, as @Grumpy_Mike said, one sample.

It depends on what you are trying to accomplish (and whether or not you're a statistician).

AWOL:

No, its not. Only static variables are initialized by the compiler. Non-statics will have a random value.

It's a global; it is initialised to zero.
Happily, the float representation of zero is the same as int or long.

You're right, I just checked the spec. My bad.

I am getting speed readings several times each second from a transducer. Each of these readings tends to vary a bit from the prior one, and I just want to get a stable reading to use to present to the driver.

This works nicely. Thanks.

Seems like it can be used for minor potentiometer output jitter. If I initialize smooth to the same value of the pot, it starts the calculation there, which is good.

I now see the relationship between the two side of that formula. One side is fast to react, the other is slow but better at smoothing. Like the petrol needle in your car, very good at smoothing, but too slow to be used for updating a value based on a pot turning.

In case anyone wants to try this easily, here's my test code.
If you change the pot value - which has +5/-5 value jitter added - you'll quickly see the data output of 'smooth' stabilize.

float smooth; 
int randomized_potval;

void setup() 
{
  smooth = analogRead(5);  // grab sensor value to be initial value in calculation.
  Serial.begin(115200);
}


void loop() 
{
  float potval = analogRead(5);   // read pot on pin 5
  randomized_potval = random( potval - 5, potval + 5);  // add some jitter

  smooth = (0.99 * smooth) + (0.01 * randomized_potval);  // smooth it out

  serial.print(randomized_potval);              // show jittered version of analog 5 value
  serial.print(" ");
  serial.println(int(smooth));            // OUTPUT -  we are looking for this smoothed number to be stable.

  delay (2);
}

skyjumper:
Currently I am storing the last 20 samples and averaging them, but I have been looking for a way to achieve this without consuming 80 bytes (20 floats)... I am getting speed readings several times each second from a transducer. Each of these readings tends to vary a bit from the prior one, and I just want to get a stable reading to use to present to the driver.

α = 0.25 gives a window that almost decays away at 20 samples and can be implemented without floating-point. I think this will work...

unsigned long history;
unsigned short value;

void setup( void )
{
  Serial.begin( 250000 );
  history = analogRead( 0 ) * 4;
}

void loop( void )
{
  history = analogRead( 0 ) + (((3 * history) + 2) / 4);
  value = (history + 2) / 4;

  Serial.println( value );

  delay( 100 );
}

Edit: added rounding.

Thanks!!! I'll play with that...

I think dot-8 rather than dot-2 fixed-point may give slightly more accurate results. Try this one instead...

unsigned long history;
unsigned short value;

void setup( void )
{
  Serial.begin( 250000 );
  history = analogRead( 0 ) * 256;
}

void loop( void )
{
  history = (64*analogRead(0)) + (((64*3*history)+128) / 256);
  value = (history + 128) / 256;

  Serial.println( value );

  delay( 100 );
}

Edit: added rounding.

This looks very interesting, but I don't seem to follow the formula.

Can you explain what it's doing?

The basic formula is...
v1 = (α * analogRead) + ((1 - α) * v0)

α = 0.25 or 1/4 ...
v1 = ((1/4) * analogRead) + ((1 - (1/4)) * v0)
v1 = ((1/4) * analogRead) + ((3/4) * v0)

To make it fixed-point with eight bits for the fraction multiple both sides by 256 (2 to the power of 8)...
256v1 = 256 * { ((1/4) * analogRead) + ((3/4) * v0) }
256
v1 = ((256/4) * analogRead) + ((3256/4) * v0)
256
v1 = ((64) * analogRead) + ((3*64) * v0)

The right-side has "v0" not "256v0" so we have to perform the division when calculating the next value. The multiplication is performed first to preserve the precision...
256
v1 = (64 * analogRead) + ((364v0) / 256)

Finally, to improve the accuracy we need to include rounding...
256v1 = (64 * analogRead) + (((364*v0)+(256/2)) / 256)

So, history is the "actual" value multiplied by 256. Another way to look it: history / 256 is the whole number part and history % 256 is the fractional part.

Nice!

Going back to the original, is the big disavantage that you have to use a float?

Is that much slower? How much?

Float is a lot slower, but I haven't got figures to say exactly how much. At least four times slower.