use linear regression for preduction
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29223c0070
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1564860213
@ -2,6 +2,7 @@
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#include "freertos/task.h"
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#include "driver/gpio.h"
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#include <string.h>
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#include <math.h>
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#include "esp_log.h"
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#include <ds18x20.h>
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@ -35,6 +36,7 @@ void taskInput(void *pvParameters);
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void initMeasurement(sMeasurement *pMeasurement);
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void updateAverage(sMeasurement *pMeasurement);
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void updatePrediction(sMeasurement *pMeasurement);
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float linearRegressionPredict(const float *samples, size_t count, float futureIndex);
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void initInputs(void)
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{
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@ -82,6 +84,9 @@ void initInputs(void)
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void initMeasurement(sMeasurement *pMeasurement)
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{
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if (!pMeasurement)
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return;
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pMeasurement->state = MEASUREMENT_FAULT;
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pMeasurement->fCurrentValue = 0.0f;
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@ -95,11 +100,6 @@ void initMeasurement(sMeasurement *pMeasurement)
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pMeasurement->average60s.bufferIndex = 0U;
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memset(pMeasurement->average60s.samples, 0U, AVG60_SAMPLE_SIZE);
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pMeasurement->predict10s.fValue = 0.0f;
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pMeasurement->predict10s.bufferCount = 0U;
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pMeasurement->predict10s.bufferIndex = 0U;
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memset(pMeasurement->predict10s.samples, 0U, PRED10_SAMPLE_SIZE);
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pMeasurement->predict60s.fValue = 0.0f;
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pMeasurement->predict60s.bufferCount = 0U;
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pMeasurement->predict60s.bufferIndex = 0U;
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@ -107,7 +107,11 @@ void initMeasurement(sMeasurement *pMeasurement)
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}
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void updateAverage(sMeasurement *pMeasurement)
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{ /* Average form the last 10sec */
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{
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if (!pMeasurement)
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return;
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// Average form the last 10sec
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pMeasurement->average10s.samples[pMeasurement->average10s.bufferIndex] = pMeasurement->fCurrentValue;
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pMeasurement->average10s.bufferIndex = (pMeasurement->average10s.bufferIndex + 1) % AVG10_SAMPLE_SIZE;
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@ -124,7 +128,7 @@ void updateAverage(sMeasurement *pMeasurement)
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pMeasurement->average10s.fValue = sum / pMeasurement->average10s.bufferCount;
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/* Average form the last 60sec */
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// Average form the last 60sec
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pMeasurement->average60s.samples[pMeasurement->average60s.bufferIndex] = pMeasurement->fCurrentValue;
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pMeasurement->average60s.bufferIndex = (pMeasurement->average60s.bufferIndex + 1) % AVG60_SAMPLE_SIZE;
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@ -148,35 +152,22 @@ void updateAverage(sMeasurement *pMeasurement)
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}
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void updatePrediction(sMeasurement *pMeasurement)
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{ /* Prediction of the value in 10sec */
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pMeasurement->predict10s.samples[pMeasurement->predict10s.bufferIndex] = pMeasurement->fCurrentValue;
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pMeasurement->predict10s.bufferIndex = (pMeasurement->predict10s.bufferIndex + 1) % PRED10_SAMPLE_SIZE;
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{
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if (!pMeasurement)
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return;
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if (pMeasurement->predict10s.bufferCount < PRED10_SAMPLE_SIZE)
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{
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pMeasurement->predict10s.bufferCount++;
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}
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// Update predict60s buffer
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sPredict *predict60s = &pMeasurement->predict60s;
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predict60s->samples[predict60s->bufferIndex] = pMeasurement->fCurrentValue;
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predict60s->bufferIndex = (predict60s->bufferIndex + 1) % PRED60_SAMPLE_SIZE;
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if (predict60s->bufferCount < PRED60_SAMPLE_SIZE)
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predict60s->bufferCount++;
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float delta10s = pMeasurement->predict10s.samples[(pMeasurement->predict10s.bufferIndex - 1) % PRED10_SAMPLE_SIZE] - pMeasurement->predict10s.samples[pMeasurement->predict10s.bufferIndex];
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if (delta10s != 0.0)
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{
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pMeasurement->predict10s.fValue = pMeasurement->fCurrentValue + (delta10s * pMeasurement->predict10s.bufferCount);
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}
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/* Prediction of the value in 60sec */
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pMeasurement->predict60s.samples[pMeasurement->predict60s.bufferIndex] = pMeasurement->fCurrentValue;
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pMeasurement->predict60s.bufferIndex = (pMeasurement->predict60s.bufferIndex + 1) % PRED60_SAMPLE_SIZE;
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if (pMeasurement->predict60s.bufferCount < PRED60_SAMPLE_SIZE)
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{
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pMeasurement->predict60s.bufferCount++;
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}
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float delta60s = pMeasurement->predict60s.samples[(pMeasurement->predict60s.bufferIndex - 1) % PRED60_SAMPLE_SIZE] - pMeasurement->predict60s.samples[pMeasurement->predict60s.bufferIndex];
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if (delta60s != 0.0)
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{
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pMeasurement->predict60s.fValue = pMeasurement->fCurrentValue + (delta60s * pMeasurement->predict60s.bufferCount);
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}
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// Predict 60s future value using linear regression
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predict60s->fValue = linearRegressionPredict(
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predict60s->samples,
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predict60s->bufferCount,
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predict60s->bufferCount + 60.0f);
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}
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void taskInput(void *pvParameters)
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@ -275,6 +266,36 @@ void taskInput(void *pvParameters)
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}
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}
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float linearRegressionPredict(const float *samples, size_t count, float futureIndex)
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{
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if (count == 0)
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return 0.0f; // No prediction possible with no data
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float sumX = 0.0f, sumY = 0.0f, sumXY = 0.0f, sumX2 = 0.0f;
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for (size_t i = 0; i < count; i++)
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{
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float x = (float)i; // Time index
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float y = samples[i]; // Sample value
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sumX += x;
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sumY += y;
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sumXY += x * y;
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sumX2 += x * x;
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}
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// Calculate slope (m) and intercept (b) of the line: y = mx + b
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float denominator = (count * sumX2 - sumX * sumX);
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if (fabs(denominator) < 1e-6) // Avoid division by zero
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return samples[count - 1]; // Return last value as prediction
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float m = (count * sumXY - sumX * sumY) / denominator;
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float b = (sumY - m * sumX) / count;
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// Predict value at futureIndex
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return m * futureIndex + b;
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}
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sMeasurement getChamberTemperature(void)
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{
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sMeasurement ret;
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#define MAX(a, b) ((a) > (b) ? (a) : (b))
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#define AVG10_SAMPLE_SIZE 10U
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#define AVG60_SAMPLE_SIZE 60U
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#define PRED10_SAMPLE_SIZE 10U
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#define PRED60_SAMPLE_SIZE 60U
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typedef enum _BurnerErrorState
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@ -29,7 +28,7 @@ typedef struct _Average
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typedef struct _Predict
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{
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float fValue;
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float samples[MAX(PRED10_SAMPLE_SIZE, PRED60_SAMPLE_SIZE)];
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float samples[PRED60_SAMPLE_SIZE];
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size_t bufferIndex;
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size_t bufferCount;
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} sPredict;
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@ -39,7 +38,6 @@ typedef struct _Measurement
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float fCurrentValue;
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sAverage average10s;
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sAverage average60s;
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sPredict predict10s;
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sPredict predict60s;
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eMeasurementErrorState state;
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} sMeasurement;
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aMetrics[u16MetricCounter].fMetricValue = getChamberTemperature().average60s.fValue;
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u16MetricCounter++;
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// Chamber Temperature Predict 10s
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strcpy(aMetrics[u16MetricCounter].caMetricName, "chamber_temperature_pred10");
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aMetrics[u16MetricCounter].type = FLOAT;
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aMetrics[u16MetricCounter].fMetricValue = getChamberTemperature().predict10s.fValue;
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u16MetricCounter++;
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// Chamber Temperature Predict 60s
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strcpy(aMetrics[u16MetricCounter].caMetricName, "chamber_temperature_pred60");
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aMetrics[u16MetricCounter].type = FLOAT;
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