Sungwoo Kim
distribution-201229
Diff: main.cpp
- Revision:
- 171:bfc1fd2629d8
- Parent:
- 170:42c938a40313
- Child:
- 172:63af34265fe9
--- a/main.cpp Wed Nov 18 12:03:39 2020 +0000
+++ b/main.cpp Sat Nov 21 07:15:47 2020 +0000
@@ -1,4 +1,4 @@
-//201118_1
+//201121_1
#include "mbed.h"
#include "FastPWM.h"
#include "INIT_HW.h"
@@ -112,7 +112,7 @@
MODE_VALVE_OPEN_LOOP, //3
MODE_JOINT_ADAPTIVE_BACKSTEPPING, //4
- MODE_VALVE_POSITION_TORQUE_CONTROL_LEARNING, //5
+ MODE_RL, //5
MODE_JOINT_POSITION_PRES_CONTROL_PWM, //6
MODE_JOINT_POSITION_PRES_CONTROL_VALVE_POSITION, //7
@@ -124,7 +124,7 @@
MODE_CURRENT_CONTROL, //11
MODE_JOINT_POSITION_TORQUE_CONTROL_CURRENT, //12
MODE_JOINT_POSITION_PRES_CONTROL_CURRENT, //13
- MODE_RL, //14
+ MODE_VALVE_POSITION_TORQUE_CONTROL_LEARNING, //14
//utility
MODE_TORQUE_SENSOR_NULLING = 20, //20
@@ -268,27 +268,27 @@
float input_RL[num_input_RL] = { 0.0f };
//Critic Networks
-float hc1[num_input_RL][10] = {0.0f};
-float bc1[10] = {0.0f};
-float hc2[10] = {0.0f};
+float hc1[num_input_RL][num_hidden_unit] = {0.0f};
+float bc1[num_hidden_unit] = {0.0f};
+float hc2[num_hidden_unit] = {0.0f};
float bc2 = 0.0f;
//Critic Networks Temporary
-float hc1_temp[num_input_RL][10] = {0.0f};
-float bc1_temp[10] = {0.0f};
-float hc2_temp[10] = {0.0f};
+float hc1_temp[num_input_RL][num_hidden_unit] = {0.0f};
+float bc1_temp[num_hidden_unit] = {0.0f};
+float hc2_temp[num_hidden_unit] = {0.0f};
float bc2_temp = 0.0f;
//Actor Networks
-float ha1[num_input_RL][10] = {0.0f};
-float ba1[10] = {0.0f};
-float ha2[10][2] = {0.0f};
+float ha1[num_input_RL][num_hidden_unit] = {0.0f};
+float ba1[num_hidden_unit] = {0.0f};
+float ha2[num_hidden_unit][2] = {0.0f};
float ba2[2] = {0.0f};
//Actor Networks Temporary
-float ha1_temp[num_input_RL][10] = {0.0f};
-float ba1_temp[10] = {0.0f};
-float ha2_temp[10][2] = {0.0f};
+float ha1_temp[num_input_RL][num_hidden_unit] = {0.0f};
+float ba1_temp[num_hidden_unit] = {0.0f};
+float ha2_temp[num_hidden_unit][2] = {0.0f};
float ba2_temp[2] = {0.0f};
float VALVE_POS_RAW_NN = 0.0f;
@@ -297,16 +297,16 @@
float Critic_Network(float *arr)
{
- float output1[10] = { 0.0f };
+ float output1[num_hidden_unit] = { 0.0f };
float output = 0.0f;
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
output1[index2] = output1[index2] + hc1[index1][index2] * arr[index1];
}
output1[index2] = tanh(output1[index2] + bc1[index2]);
}
for (int index2 = 0; index2 < 1; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
output = output + hc2[index1] * output1[index1];
}
output = output + bc2;
@@ -316,16 +316,16 @@
float Critic_Network_Temp(float *arr)
{
- float output1[10] = { 0.0f };
+ float output1[num_hidden_unit] = { 0.0f };
float output = 0.0f;
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
output1[index2] = output1[index2] + hc1_temp[index1][index2] * arr[index1];
}
output1[index2] = tanh(output1[index2] + bc1_temp[index2]);
}
for (int index2 = 0; index2 < 1; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
output = output + hc2_temp[index1] * output1[index1];
}
output = output + bc2_temp;
@@ -336,10 +336,10 @@
void Actor_Network(float *arr)
{
- float output1[10] = {0.0f};
+ float output1[num_hidden_unit] = {0.0f};
float output[2] = {0.0f};
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
output1[index2] = output1[index2] + ha1[index1][index2] * arr[index1];
}
@@ -349,49 +349,34 @@
}
}
for (int index2 = 0; index2 < 2; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
output[index2] = output[index2] + ha2[index1][index2] * output1[index1];
}
}
- mean_before_SP = output[0] + ba2[0];
+ mean_before_SP = output[0] + ba2[0]; //SP = softplus
deviation_before_SP = output[1] + ba2[1];
- mean = log(1.0f+exp(mean_before_SP));
- deviation = log(1.0f+exp(deviation_before_SP));
-}
-
-
-//void Actor_Network_Temp(float *arr)
-//{
-// float output1[10] = {0.0f};
-// float output[2] = {0.0f};
-//
-// for (int index2 = 0; index2 < 10; index2++) {
-// for (int index1 = 0; index1 < num_input_RL; index1++) {
-// output1[index2] = output1[index2] + ha1_temp[index1][index2] * arr[index1];
-// }
-// output1[index2] = output1[index2] + ba1_temp[index2];
-// if (output1[index2] < 0) {
-// output1[index2] = 0;
-// }
-// }
-// for (int index2 = 0; index2 < 2; index2++) {
-// for (int index1 = 0; index1 < 10; index1++) {
-// output[index2] = output[index2] + ha2_temp[index1][index2] * output1[index1];
-// }
-// }
-// mean_before_SP = output[0] + ba2_temp[0];
-// deviation_before_SP = output[1] + ba2_temp[1];
// mean = log(1.0f+exp(mean_before_SP));
// deviation = log(1.0f+exp(deviation_before_SP));
-//}
+ if (mean_before_SP >=0) {
+ mean = mean_before_SP;
+ } else {
+ mean = 0.0f;
+ }
+ if (deviation_before_SP >=0) {
+ deviation = deviation_before_SP;
+ } else {
+ deviation = 0.0f;
+ }
+
+}
void Actor_Network_Old(float *arr)
{
- float output1[10] = {0.0f};
+ float output1[num_hidden_unit] = {0.0f};
float output[2] = {0.0f};
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
output1[index2] = output1[index2] + ha1[index1][index2] * arr[index1];
}
@@ -401,14 +386,24 @@
}
}
for (int index2 = 0; index2 < 2; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
output[index2] = output[index2] + ha2[index1][index2] * output1[index1];
}
}
mean_old = output[0] + ba2[0];
deviation_old = output[1] + ba2[1];
- mean_old = log(1.0f+exp(mean_old));
- deviation_old = log(1.0f+exp(deviation_old));
+// mean_old = log(1.0f+exp(mean_old));
+// deviation_old = log(1.0f+exp(deviation_old));
+ if (mean_before_SP >=0) {
+ mean = mean_before_SP;
+ } else {
+ mean = 0.0f;
+ }
+ if (deviation_before_SP >=0) {
+ deviation = deviation_before_SP;
+ } else {
+ deviation = 0.0f;
+ }
}
float Grad_Normal_Dist_Mean(float mean, float deviation, float action)
@@ -429,9 +424,9 @@
{
float gradient_rate = 0.01f;
- float G_hc1[num_input_RL][10] = {0.0f};
- float G_bc1[10] = {0.0f};
- for (int index2 = 0; index2 < 10; index2++) {
+ float G_hc1[num_input_RL][num_hidden_unit] = {0.0f};
+ float G_bc1[num_hidden_unit] = {0.0f};
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
for (int i=0; i<batch_size; i++) {
float hx_sum = 0.0f;
@@ -462,10 +457,10 @@
bc1_temp[index2] = bc1_temp[index2] - gradient_rate * G_bc1[index2];
}
- float G_hc2[10] = {0.0f};
+ float G_hc2[num_hidden_unit] = {0.0f};
float G_bc2 = 0.0f;
for (int index2 = 0; index2 < 1; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
for (int i=0; i<batch_size; i++) {
float hx_sum = 0.0f;
float hx_sum_next = 0.0f;
@@ -491,26 +486,41 @@
void update_Actor_Networks(float (*arr)[num_input_RL])
{
- float gradient_rate = -0.01f;
+ float gradient_rate = 0.01f; //-0.01f
- float G_ha1[num_input_RL][10] = {0.0f};
- float G_ba1[10] = {0.0f};
- for (int index2 = 0; index2 < 10; index2++) {
+ float G_ha1[num_input_RL][num_hidden_unit] = {0.0f};
+ float G_ba1[num_hidden_unit] = {0.0f};
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
for (int i=0; i<batch_size; i++) {
if((advantage[i] >= 0.0f && ratio[i] >= 1.0f + epsilon) || (advantage[i] < 0.0f && ratio[i] < 1.0f - epsilon)) {
G_ha1[index1][index2] = G_ha1[index1][index2];
} else {
- float hx_sum = 0.0f;
- for(int j=0; j<num_input_RL; j++) {
- hx_sum = hx_sum + ha1_temp[j][index2]*arr[i][j];
+
+ float hx_sum_total = 0.0f;
+ for(int m = 0; m < num_hidden_unit; m++) {
+ for(int n = 0; n < num_input_RL; n++) {
+ hx_sum_total = hx_sum_total + ha1_temp[n][m]*arr[i][n];
+ }
}
- hx_sum = hx_sum + bc1_temp[index2];
+ hx_sum_total = hx_sum_total + bc1_temp[index2];
float d_mean_d_ha1 = 0.0f;
float d_dev_d_ha1 = 0.0f;
- if (hx_sum >= 0) {
- d_mean_d_ha1 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*ha2_temp[index2][0]*arr[i][index1];
- d_dev_d_ha1 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*ha2_temp[index2][1]*arr[i][index1];
+ if (hx_sum_total >=0) {
+ float hx_sum = 0.0f;
+ for(int j=0; j<num_input_RL; j++) {
+ hx_sum = hx_sum + ha1_temp[j][index2]*arr[i][j];
+ }
+ hx_sum = hx_sum + bc1_temp[index2];
+ if (hx_sum >= 0) {
+// d_mean_d_ha1 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*ha2_temp[index2][0]*arr[i][index1];
+// d_dev_d_ha1 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*ha2_temp[index2][1]*arr[i][index1];
+ d_mean_d_ha1 = ha2_temp[index2][0]*arr[i][index1];
+ d_dev_d_ha1 = ha2_temp[index2][1]*arr[i][index1];
+ } else {
+ d_mean_d_ha1 = 0.0f;
+ d_dev_d_ha1 = 0.0f;
+ }
} else {
d_mean_d_ha1 = 0.0f;
d_dev_d_ha1 = 0.0f;
@@ -525,16 +535,33 @@
if((advantage[i] >= 0.0f && ratio[i] >= 1.0f + epsilon) || (advantage[i] < 0.0f && ratio[i] < 1.0f - epsilon)) {
G_ba1[index2] = G_ba1[index2];
} else {
- float hx_sum = 0.0f;
- for(int j=0; j<num_input_RL; j++) {
- hx_sum = hx_sum + ha1_temp[j][index2]*arr[i][j];
+
+ float hx_sum_total = 0.0f;
+ for(int m = 0; m < num_hidden_unit; m++) {
+ for(int n = 0; n < num_input_RL; n++) {
+ hx_sum_total = hx_sum_total + ha1_temp[n][m]*arr[i][n];
+ }
}
- hx_sum = hx_sum + bc1_temp[index2];
+ hx_sum_total = hx_sum_total + bc1_temp[index2];
float d_mean_d_ba1 = 0.0f;
float d_dev_d_ba1 = 0.0f;
- if(hx_sum >=0) {
- d_mean_d_ba1 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*ha2_temp[index2][0];
- d_dev_d_ba1 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*ha2_temp[index2][1];
+ if (hx_sum_total >=0) {
+
+ float hx_sum = 0.0f;
+ for(int j=0; j<num_input_RL; j++) {
+ hx_sum = hx_sum + ha1_temp[j][index2]*arr[i][j];
+ }
+ hx_sum = hx_sum + bc1_temp[index2];
+
+ if(hx_sum >=0) {
+// d_mean_d_ba1 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*ha2_temp[index2][0];
+// d_dev_d_ba1 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*ha2_temp[index2][1];
+ d_mean_d_ba1 = ha2_temp[index2][0];
+ d_dev_d_ba1 = ha2_temp[index2][1];
+ } else {
+ d_mean_d_ba1 = 0.0f;
+ d_dev_d_ba1 = 0.0f;
+ }
} else {
d_mean_d_ba1 = 0.0f;
d_dev_d_ba1 = 0.0f;
@@ -546,27 +573,42 @@
ba1_temp[index2] = ba1_temp[index2] - gradient_rate * G_ba1[index2];
}
- float G_ha2[10][2] = {0.0f};
+ float G_ha2[num_hidden_unit][2] = {0.0f};
float G_ba2[2] = {0.0f};
for (int index2 = 0; index2 < 2; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
for (int i=0; i<batch_size; i++) {
if((advantage[i] >= 0.0f && ratio[i] >= 1.0f + epsilon) || (advantage[i] < 0.0f && ratio[i] < 1.0f - epsilon)) {
G_ha2[index1][index2] = G_ha2[index1][index2];
} else {
- float hx_sum = 0.0f;
- for(int j=0; j<num_input_RL; j++) {
- hx_sum = hx_sum + ha1_temp[j][index1]*arr[i][j];
+
+ float hx_sum_total = 0.0f;
+ for(int m = 0; m < num_hidden_unit; m++) {
+ for(int n = 0; n < num_input_RL; n++) {
+ hx_sum_total = hx_sum_total + ha1_temp[n][m]*arr[i][n];
+ }
}
- hx_sum = hx_sum + bc1_temp[index1];
+ hx_sum_total = hx_sum_total + bc1_temp[index2];
float d_mean_d_ha2 = 0.0f;
float d_dev_d_ha2 = 0.0f;
- if (hx_sum >= 0) {
- d_mean_d_ha2 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*hx_sum;
- d_dev_d_ha2 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*hx_sum;
+ if (hx_sum_total >=0) {
+ float hx_sum = 0.0f;
+ for(int j=0; j<num_input_RL; j++) {
+ hx_sum = hx_sum + ha1_temp[j][index1]*arr[i][j];
+ }
+ hx_sum = hx_sum + bc1_temp[index1];
+ if (hx_sum >= 0) {
+// d_mean_d_ha2 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]))*hx_sum;
+// d_dev_d_ha2 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]))*hx_sum;
+ d_mean_d_ha2 = hx_sum;
+ d_dev_d_ha2 = hx_sum;
+ } else {
+ d_mean_d_ha2 = 0.0f;
+ d_mean_d_ha2 = 0.0f;
+ }
} else {
d_mean_d_ha2 = 0.0f;
- d_dev_d_ha2 = 0.0f;
+ d_mean_d_ha2 = 0.0f;
}
G_ha2[index1][index2] = G_ha2[index1][index2] + advantage[i]/pi_old[i]*(d_mean_d_ha2*Grad_Normal_Dist_Mean(mean_array[i],deviation_array[i],action_array[i])+d_dev_d_ha2*Grad_Normal_Dist_Deviation(mean_array[i],deviation_array[i],action_array[i]));
}
@@ -581,8 +623,10 @@
float d_mean_d_ba2 = 0.0f;
float d_dev_d_ba2 = 0.0f;
- d_mean_d_ba2 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]));
- d_dev_d_ba2 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]));
+// d_mean_d_ba2 = exp(mean_before_SP_array[i])/(1.0f+exp(mean_before_SP_array[i]));
+// d_dev_d_ba2 = exp(deviation_before_SP_array[i])/(1.0f+exp(deviation_before_SP_array[i]));
+ d_mean_d_ba2 = 1.0f;
+ d_dev_d_ba2 = 1.0f;
G_ba1[index2] = G_ba1[index2] + advantage[i]/pi_old[i]*(d_mean_d_ba2*Grad_Normal_Dist_Mean(mean_array[i],deviation_array[i],action_array[i])+d_dev_d_ba2*Grad_Normal_Dist_Deviation(mean_array[i],deviation_array[i],action_array[i]));
}
}
@@ -622,7 +666,7 @@
void Overwirte_Critic_Networks()
{
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
hc1[index1][index2] = hc1_temp[index1][index2];
}
@@ -633,14 +677,14 @@
}
void Overwirte_Actor_Networks()
{
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
ha1[index1][index2] = ha1_temp[index1][index2];
}
ba1[index2] = ba1_temp[index2];
}
for (int index2 = 0; index2 < 2; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
ha2[index1][index2] = ha2_temp[index1][index2];
}
ba2[index2] = ba2_temp[index2];
@@ -731,7 +775,7 @@
ID_index_array[i] = (i+1) * 0.5f;
}
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
hc1_temp[index1][index2] = (float) (rand()%100) * 0.01f ;
}
@@ -739,19 +783,19 @@
hc2_temp[index2] = (float) (rand()%100) * 0.01f;
}
bc2_temp = (float) (rand()%100) * 0.01f;
- for (int index2 = 0; index2 < 10; index2++) {
+ for (int index2 = 0; index2 < num_hidden_unit; index2++) {
for (int index1 = 0; index1 < num_input_RL; index1++) {
ha1_temp[index1][index2] = (float) (rand()%100) * 0.01f;
}
ba1_temp[index2] = (float) (rand()%100) * 0.01f;
}
for (int index2 = 0; index2 < 2; index2++) {
- for (int index1 = 0; index1 < 10; index1++) {
+ for (int index1 = 0; index1 < num_hidden_unit; index1++) {
ha2_temp[index1][index2] = (float) (rand()%100) * 0.01f;
}
ba2_temp[index2] = (float) (rand()%100) * 0.01f;
}
-
+
Overwirte_Critic_Networks();
Overwirte_Actor_Networks();
@@ -759,20 +803,21 @@
*** Program is operating!
*************************************/
while(1) {
-// if(timer_while==1000 && OPERATING_MODE==5) {
- //if(timer_while==1000) {
- //i2c
- read_field(i2c_slave_addr1);
- if(DIR_VALVE_ENC < 0) value = 1023 - value;
- // if(LED==1) {
- // LED=0;
- // } else
- // LED = 1;
- timer_while = 0;
- //}
+// if(timer_while==27491) {
+// timer_while = 0;
+// pc.printf("ref : %f virt_pos : %f mean : %f deviation : %f Last_pos_of_batch : %f reward_sum : %f\n", pos.sen/(float)(ENC_PULSE_PER_POSITION), logging3, logging2, logging4, logging1, logging5);
+// //pc.printf("%f\n", virt_pos);
+// //pc.printf("%f\n", pos.sen/(float)(ENC_PULSE_PER_POSITION));
+// //pc.printf("ref : %f virt_pos : %f\n", pos.sen/(float)(ENC_PULSE_PER_POSITION), virt_pos);
+// }
- timer_while ++;
+
+ //i2c
+ //read_field(i2c_slave_addr1);
+ //if(DIR_VALVE_ENC < 0) value = 1023 - value;
+
+// timer_while ++;
///////////////////////////////////////////////////////Neural Network
@@ -874,8 +919,8 @@
LED = 1;
}
-
-
+
+
/////////////////////////////////////////////////////////////////////RL
switch (Update_Case) {
case 0: {
@@ -886,7 +931,6 @@
for (int epoch = 0; epoch < num_epoch; epoch++) {
float loss_sum = 0.0f;
for (int i=batch_size-1; i>=0; i--) {
- V[batch_size] = 0.0f;
//Calculate Estimated V
//float temp_array[3] = {state_array[i][0], state_array[i][1], state_array[i][2]};
float temp_array[2] = {state_array[i][0], state_array[i][1]};
@@ -894,7 +938,7 @@
pi[i] = exp(-(action_array[i]-mean_array[i])*(action_array[i]-mean_array[i])/(2.0f*deviation_array[i]*deviation_array[i]))/(sqrt(2.0f*PI)*deviation_array[i]);
Actor_Network_Old(temp_array);
pi_old[i] = exp(-(action_array[i]-mean_old)*(action_array[i]-mean_old)/(2.0f*deviation_old*deviation_old))/(sqrt(2.0f*PI)*deviation_old);
- r[i] = exp(-0.01f * state_array[i][1] * 70.0f * state_array[i][1] * 70.0f);
+ r[i] = exp(-0.00005f * state_array[i][1] * 70.0f * state_array[i][1] * 70.0f);
if(i == batch_size-1) td_target[i] = r[i];
else td_target[i] = r[i] + gamma * V[i+1];
delta[i] = td_target[i] - V[i];
@@ -917,8 +961,8 @@
reward_sum = reward_sum + r[i];
}
logging5 = reward_sum;
-
-
+
+
//loss_batch = loss_sum / (float) batch_size;
loss_batch = loss_sum;
//Update Networks
@@ -929,7 +973,7 @@
Update_Done_Flag = 1;
Update_Case = 0;
//logging1 = V[0];
-
+
break;
}
case 2: {
@@ -2311,7 +2355,7 @@
gamma_hat = gamma_hat + gamma_hat_dot / (float) TMR_FREQ_5k;
break;
}
-
+
case MODE_RL: {
//t.reset();
//t.start();
@@ -2344,7 +2388,7 @@
} else if(virt_pos < -70.0f) {
virt_pos = -70.0f;
}
-
+
RL_timer++;
@@ -2563,9 +2607,9 @@
}
- if (flag_data_request[2] == LOW) {
+ if (flag_data_request[2] == HIGH) {
double t_value = 0.0f;
- if(valve_pos.ref>=(float) VALVE_CENTER) {
+ if(value>=(float) VALVE_CENTER) {
t_value = 10000.0f*((double)value - (double)VALVE_CENTER)/((double)VALVE_MAX_POS - (double)VALVE_CENTER);
} else {
t_value = -10000.0f*((double)value - (double)VALVE_CENTER)/((double)VALVE_MIN_POS - (double)VALVE_CENTER);
@@ -2596,7 +2640,7 @@
// }
if (flag_data_request[4] == HIGH) {
//valve position
- CAN_TX_VALVE_POSITION((int16_t) (input_NN[1] * 100.0f), (int16_t) (input_NN[2]* 100.0f), (int16_t) (input_NN[3]* 100.0f), (int16_t) (input_NN[4]* 100.0f)); //1600
+ CAN_TX_VALVE_POSITION((int16_t) pos.sen/(float)(ENC_PULSE_PER_POSITION), (int16_t) virt_pos, (int16_t) 0, (int16_t) 0); //1600
}
// Others : Reference position, Reference FT, PWM, Current (ID:1300)