use linear regression for preduction

This commit is contained in:
Hendrik Schutter 2024-12-26 18:49:04 +01:00
parent 29223c0070
commit 1564860213
3 changed files with 56 additions and 43 deletions

View File

@ -2,6 +2,7 @@
#include "freertos/task.h"
#include "driver/gpio.h"
#include <string.h>
#include <math.h>
#include "esp_log.h"
#include <ds18x20.h>
@ -35,6 +36,7 @@ void taskInput(void *pvParameters);
void initMeasurement(sMeasurement *pMeasurement);
void updateAverage(sMeasurement *pMeasurement);
void updatePrediction(sMeasurement *pMeasurement);
float linearRegressionPredict(const float *samples, size_t count, float futureIndex);
void initInputs(void)
{
@ -82,6 +84,9 @@ void initInputs(void)
void initMeasurement(sMeasurement *pMeasurement)
{
if (!pMeasurement)
return;
pMeasurement->state = MEASUREMENT_FAULT;
pMeasurement->fCurrentValue = 0.0f;
@ -95,11 +100,6 @@ void initMeasurement(sMeasurement *pMeasurement)
pMeasurement->average60s.bufferIndex = 0U;
memset(pMeasurement->average60s.samples, 0U, AVG60_SAMPLE_SIZE);
pMeasurement->predict10s.fValue = 0.0f;
pMeasurement->predict10s.bufferCount = 0U;
pMeasurement->predict10s.bufferIndex = 0U;
memset(pMeasurement->predict10s.samples, 0U, PRED10_SAMPLE_SIZE);
pMeasurement->predict60s.fValue = 0.0f;
pMeasurement->predict60s.bufferCount = 0U;
pMeasurement->predict60s.bufferIndex = 0U;
@ -107,7 +107,11 @@ void initMeasurement(sMeasurement *pMeasurement)
}
void updateAverage(sMeasurement *pMeasurement)
{ /* Average form the last 10sec */
{
if (!pMeasurement)
return;
// Average form the last 10sec
pMeasurement->average10s.samples[pMeasurement->average10s.bufferIndex] = pMeasurement->fCurrentValue;
pMeasurement->average10s.bufferIndex = (pMeasurement->average10s.bufferIndex + 1) % AVG10_SAMPLE_SIZE;
@ -124,7 +128,7 @@ void updateAverage(sMeasurement *pMeasurement)
pMeasurement->average10s.fValue = sum / pMeasurement->average10s.bufferCount;
/* Average form the last 60sec */
// Average form the last 60sec
pMeasurement->average60s.samples[pMeasurement->average60s.bufferIndex] = pMeasurement->fCurrentValue;
pMeasurement->average60s.bufferIndex = (pMeasurement->average60s.bufferIndex + 1) % AVG60_SAMPLE_SIZE;
@ -148,35 +152,22 @@ void updateAverage(sMeasurement *pMeasurement)
}
void updatePrediction(sMeasurement *pMeasurement)
{ /* Prediction of the value in 10sec */
pMeasurement->predict10s.samples[pMeasurement->predict10s.bufferIndex] = pMeasurement->fCurrentValue;
pMeasurement->predict10s.bufferIndex = (pMeasurement->predict10s.bufferIndex + 1) % PRED10_SAMPLE_SIZE;
{
if (!pMeasurement)
return;
if (pMeasurement->predict10s.bufferCount < PRED10_SAMPLE_SIZE)
{
pMeasurement->predict10s.bufferCount++;
}
// Update predict60s buffer
sPredict *predict60s = &pMeasurement->predict60s;
predict60s->samples[predict60s->bufferIndex] = pMeasurement->fCurrentValue;
predict60s->bufferIndex = (predict60s->bufferIndex + 1) % PRED60_SAMPLE_SIZE;
if (predict60s->bufferCount < PRED60_SAMPLE_SIZE)
predict60s->bufferCount++;
float delta10s = pMeasurement->predict10s.samples[(pMeasurement->predict10s.bufferIndex - 1) % PRED10_SAMPLE_SIZE] - pMeasurement->predict10s.samples[pMeasurement->predict10s.bufferIndex];
if (delta10s != 0.0)
{
pMeasurement->predict10s.fValue = pMeasurement->fCurrentValue + (delta10s * pMeasurement->predict10s.bufferCount);
}
/* Prediction of the value in 60sec */
pMeasurement->predict60s.samples[pMeasurement->predict60s.bufferIndex] = pMeasurement->fCurrentValue;
pMeasurement->predict60s.bufferIndex = (pMeasurement->predict60s.bufferIndex + 1) % PRED60_SAMPLE_SIZE;
if (pMeasurement->predict60s.bufferCount < PRED60_SAMPLE_SIZE)
{
pMeasurement->predict60s.bufferCount++;
}
float delta60s = pMeasurement->predict60s.samples[(pMeasurement->predict60s.bufferIndex - 1) % PRED60_SAMPLE_SIZE] - pMeasurement->predict60s.samples[pMeasurement->predict60s.bufferIndex];
if (delta60s != 0.0)
{
pMeasurement->predict60s.fValue = pMeasurement->fCurrentValue + (delta60s * pMeasurement->predict60s.bufferCount);
}
// Predict 60s future value using linear regression
predict60s->fValue = linearRegressionPredict(
predict60s->samples,
predict60s->bufferCount,
predict60s->bufferCount + 60.0f);
}
void taskInput(void *pvParameters)
@ -275,6 +266,36 @@ void taskInput(void *pvParameters)
}
}
float linearRegressionPredict(const float *samples, size_t count, float futureIndex)
{
if (count == 0)
return 0.0f; // No prediction possible with no data
float sumX = 0.0f, sumY = 0.0f, sumXY = 0.0f, sumX2 = 0.0f;
for (size_t i = 0; i < count; i++)
{
float x = (float)i; // Time index
float y = samples[i]; // Sample value
sumX += x;
sumY += y;
sumXY += x * y;
sumX2 += x * x;
}
// Calculate slope (m) and intercept (b) of the line: y = mx + b
float denominator = (count * sumX2 - sumX * sumX);
if (fabs(denominator) < 1e-6) // Avoid division by zero
return samples[count - 1]; // Return last value as prediction
float m = (count * sumXY - sumX * sumY) / denominator;
float b = (sumY - m * sumX) / count;
// Predict value at futureIndex
return m * futureIndex + b;
}
sMeasurement getChamberTemperature(void)
{
sMeasurement ret;

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@ -3,7 +3,6 @@
#define MAX(a, b) ((a) > (b) ? (a) : (b))
#define AVG10_SAMPLE_SIZE 10U
#define AVG60_SAMPLE_SIZE 60U
#define PRED10_SAMPLE_SIZE 10U
#define PRED60_SAMPLE_SIZE 60U
typedef enum _BurnerErrorState
@ -29,7 +28,7 @@ typedef struct _Average
typedef struct _Predict
{
float fValue;
float samples[MAX(PRED10_SAMPLE_SIZE, PRED60_SAMPLE_SIZE)];
float samples[PRED60_SAMPLE_SIZE];
size_t bufferIndex;
size_t bufferCount;
} sPredict;
@ -39,7 +38,6 @@ typedef struct _Measurement
float fCurrentValue;
sAverage average10s;
sAverage average60s;
sPredict predict10s;
sPredict predict60s;
eMeasurementErrorState state;
} sMeasurement;

View File

@ -128,12 +128,6 @@ void taskMetrics(void *pvParameters)
aMetrics[u16MetricCounter].fMetricValue = getChamberTemperature().average60s.fValue;
u16MetricCounter++;
// Chamber Temperature Predict 10s
strcpy(aMetrics[u16MetricCounter].caMetricName, "chamber_temperature_pred10");
aMetrics[u16MetricCounter].type = FLOAT;
aMetrics[u16MetricCounter].fMetricValue = getChamberTemperature().predict10s.fValue;
u16MetricCounter++;
// Chamber Temperature Predict 60s
strcpy(aMetrics[u16MetricCounter].caMetricName, "chamber_temperature_pred60");
aMetrics[u16MetricCounter].type = FLOAT;