PID control - Versionsgeschichte

Alexanderg: /* PID settings */

2016-07-23T10:38:39Z

‎PID settings

Alexanderg: /* PID settings */

2016-07-23T10:38:30Z

‎PID settings

Alexanderg: /* PID settings */

2016-07-23T10:38:11Z

‎PID settings

Alexanderg: /* PID settings */

2016-07-23T10:37:24Z

‎PID settings

Alexanderg: /* Abstract */

2016-06-08T12:53:01Z

‎Abstract

Alexanderg: /* PID controller */

2016-06-03T06:32:12Z

‎PID controller

Alexanderg: /* PID settings */

2016-05-29T12:17:45Z

‎PID settings

Alexanderg: /* PID settings */

2016-05-29T10:15:18Z

‎PID settings

Alexanderg: /* PID settings */

2016-05-29T10:14:37Z

‎PID settings

Alexanderg: /* PID controller */

2016-05-29T10:14:25Z

‎PID controller

@@ Zeile 21: / Zeile 21: @@
 A PID controller takes three things into consideration:
-#Error (P): Where you want to be vs. where you are - This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
+#error (P): Where you want to be vs. where you are - This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
 #derivative (D): How fast you are approaching - If you are approaching the target quickly and you are close to it, you actually need to slow down. The derivative helps take that into consideration.
 #integral (I): Alignment error - Your robot may not actually do exactly what you tell it to do. The integral helps determine how much you need to compensate for that.

@@ Zeile 21: / Zeile 21: @@
 A PID controller takes three things into consideration:
-#Error: Where you want to be vs. where you are - This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
+#Error (P): Where you want to be vs. where you are - This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
 #derivative (D): How fast you are approaching - If you are approaching the target quickly and you are close to it, you actually need to slow down. The derivative helps take that into consideration.
 #integral (I): Alignment error - Your robot may not actually do exactly what you tell it to do. The integral helps determine how much you need to compensate for that.

@@ Zeile 21: / Zeile 21: @@
 A PID controller takes three things into consideration:
-#Error: where you want to be vs. where you are
+#Error: Where you want to be vs. where you are - This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
+#derivative (D): How fast you are approaching - If you are approaching the target quickly and you are close to it, you actually need to slow down. The derivative helps take that into consideration.
-This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
+#integral (I): Alignment error - Your robot may not actually do exactly what you tell it to do. The integral helps determine how much you need to compensate for that.
-−
-#derivative (D): how fast you are approaching
-−
 If you are approaching the target quickly and you are close to it, you actually need to slow down. The derivative helps take that into consideration.
-−
-#integral (I): alignment error
-−
 Your robot may not actually do exactly what you tell it to do. The integral helps determine how much you need to compensate for that.
-−
 The optimal P,I,D parameters depend on the actual hardware. The software default PID parameters are for the Ardumower motors available in the shop. To use your own motors, one method is trial & error (it can be difficult to find the optimum PID parameters):

← Nächstältere Version		Version vom 23. Juli 2016, 10:37 Uhr
Zeile 19:		Zeile 19:

	=PID settings=		=PID settings=
		+
		+	A PID controller takes three things into consideration:
		+	#Error: where you want to be vs. where you are
		+
		+	This is certainly a big factor. If you are at point A and your target is at point B, then the vector from A to B tells you a lot about how you need to steer, but it isn't the only factor.
		+
		+	#derivative (D): how fast you are approaching
		+
		+	If you are approaching the target quickly and you are close to it, you actually need to slow down. The derivative helps take that into consideration.
		+
		+	#integral (I): alignment error
		+
		+	Your robot may not actually do exactly what you tell it to do. The integral helps determine how much you need to compensate for that.
		+
		+
	The optimal P,I,D parameters depend on the actual hardware. The software default PID parameters are for the Ardumower motors available in the shop. To use your own motors, one method is trial & error (it can be difficult to find the optimum PID parameters):		The optimal P,I,D parameters depend on the actual hardware. The software default PID parameters are for the Ardumower motors available in the shop. To use your own motors, one method is trial & error (it can be difficult to find the optimum PID parameters):

@@ Zeile 6: / Zeile 6: @@
 * motor speed control
 * ...
 =PID controller=

@@ Zeile 9: / Zeile 9: @@
 =PID controller=
-<gallery>
+[[File: Pid_controller.png | 600px]]
-  File: Pid_controller.png | PID controller
-</gallery>
 Examples:

@@ Zeile 19: / Zeile 19: @@
 =PID settings=
-The optimal P,I,D parameters depend on the actual hardware. One method is trial & error (it can be difficult to find them):
+The optimal P,I,D parameters depend on the actual hardware. The software default PID parameters are for the Ardumower motors available in the shop. To use your own motors, one method is trial & error (it can be difficult to find the optimum PID parameters):
 # Increase P until system starts to oscillate

@@ Zeile 29: / Zeile 29: @@
   D : Determines how aggressively the PID reacts to the change in error (Derivative)
   I : Determines how aggressively the PID reacts to error over time (Integral)
 =Velocity PID=