Smoothing with Physical Constraints

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I'm wondering if there is currently an algorithm (or mathematical model) used to smooth functions keeping in mind physical constraints (say, ensuring slopes don't exceed that of a specific heating/cooling curve slope value).

I've been searching around and nothing seems to fit what I'm looking for. Essentially, I have discrete temperature values (e.g. 100, 115, 130) that are likely constant for periods of time, but can ultimately fluctuate between the three instantaneously (these values are predictions of optimal temperature at each given time step). I'm looking for ways of smoothing these large temperature increases/decreases to something that is physically obtainable by limiting the slope of the curve that connects each discrete value.

Is there something out there that would be decent for what I'm trying to do?

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asked Jul 15 at 16:39

Whisperrrr

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I'm wondering if there is currently an algorithm (or mathematical model) used to smooth functions keeping in mind physical constraints (say, ensuring slopes don't exceed that of a specific heating/cooling curve slope value).

I've been searching around and nothing seems to fit what I'm looking for. Essentially, I have discrete temperature values (e.g. 100, 115, 130) that are likely constant for periods of time, but can ultimately fluctuate between the three instantaneously (these values are predictions of optimal temperature at each given time step). I'm looking for ways of smoothing these large temperature increases/decreases to something that is physically obtainable by limiting the slope of the curve that connects each discrete value.

Is there something out there that would be decent for what I'm trying to do?

statistics

share|cite|improve this question

asked Jul 15 at 16:39

Whisperrrr

6

add a comment | 

up vote
0
down vote

favorite

up vote
0
down vote

favorite

I'm wondering if there is currently an algorithm (or mathematical model) used to smooth functions keeping in mind physical constraints (say, ensuring slopes don't exceed that of a specific heating/cooling curve slope value).

I've been searching around and nothing seems to fit what I'm looking for. Essentially, I have discrete temperature values (e.g. 100, 115, 130) that are likely constant for periods of time, but can ultimately fluctuate between the three instantaneously (these values are predictions of optimal temperature at each given time step). I'm looking for ways of smoothing these large temperature increases/decreases to something that is physically obtainable by limiting the slope of the curve that connects each discrete value.

Is there something out there that would be decent for what I'm trying to do?

statistics

share|cite|improve this question

asked Jul 15 at 16:39

Whisperrrr

6

I'm wondering if there is currently an algorithm (or mathematical model) used to smooth functions keeping in mind physical constraints (say, ensuring slopes don't exceed that of a specific heating/cooling curve slope value).

I've been searching around and nothing seems to fit what I'm looking for. Essentially, I have discrete temperature values (e.g. 100, 115, 130) that are likely constant for periods of time, but can ultimately fluctuate between the three instantaneously (these values are predictions of optimal temperature at each given time step). I'm looking for ways of smoothing these large temperature increases/decreases to something that is physically obtainable by limiting the slope of the curve that connects each discrete value.

Is there something out there that would be decent for what I'm trying to do?

statistics

share|cite|improve this question

asked Jul 15 at 16:39

Whisperrrr

6

share|cite|improve this question

share|cite|improve this question

asked Jul 15 at 16:39

Whisperrrr

6

asked Jul 15 at 16:39

Whisperrrr

6

asked Jul 15 at 16:39

Whisperrrr

6

6

add a comment | 

add a comment | 

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The easiest way to do this is probably time averaging. That is, replace the temperature at any particular time with the average of the temperatures over a fixed period of time before that time. The longer the fixed time period, the slower the rate of change when the temperature jumps to another value. You could experiment with weighted averages. Read Exponential smoothing.

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edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

active

oldest

votes

active

oldest

votes

up vote
0
down vote

The easiest way to do this is probably time averaging. That is, replace the temperature at any particular time with the average of the temperatures over a fixed period of time before that time. The longer the fixed time period, the slower the rate of change when the temperature jumps to another value. You could experiment with weighted averages. Read Exponential smoothing.

share|cite|improve this answer

edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

11.7k1933

add a comment | 

up vote
0
down vote

The easiest way to do this is probably time averaging. That is, replace the temperature at any particular time with the average of the temperatures over a fixed period of time before that time. The longer the fixed time period, the slower the rate of change when the temperature jumps to another value. You could experiment with weighted averages. Read Exponential smoothing.

share|cite|improve this answer

edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

11.7k1933

add a comment | 

up vote
0
down vote

up vote
0
down vote

The easiest way to do this is probably time averaging. That is, replace the temperature at any particular time with the average of the temperatures over a fixed period of time before that time. The longer the fixed time period, the slower the rate of change when the temperature jumps to another value. You could experiment with weighted averages. Read Exponential smoothing.

share|cite|improve this answer

edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

11.7k1933

The easiest way to do this is probably time averaging. That is, replace the temperature at any particular time with the average of the temperatures over a fixed period of time before that time. The longer the fixed time period, the slower the rate of change when the temperature jumps to another value. You could experiment with weighted averages. Read Exponential smoothing.

share|cite|improve this answer

edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

11.7k1933

share|cite|improve this answer

share|cite|improve this answer

edited Jul 17 at 14:36

edited Jul 17 at 14:36

edited Jul 17 at 14:36

answered Jul 15 at 20:02

Somos

11.7k1933

answered Jul 15 at 20:02

Somos

11.7k1933

answered Jul 15 at 20:02

Somos

11.7k1933

11.7k1933

add a comment | 

add a comment | 

 

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