smartPID 1.0

This library contains three controller algorithms.

The smartPID Library

1. Background

This library contains three kinds of PID controller algorithms, which are position PID controller, incremental PID controller and single neural PID controller. According to different scenarios, different types of controller algorithms can be called after loading the library.

2. About the author

This library is compiled by Qi Zhu from the People's Republic of China.

3. Environment

This library is written in Python 3.7.

4. Dependent Libraries

This library needs to use the time library, so before using this library, you need to make sure that your environment already contains the time library.

5. How to use the library

The first step is to download the library.

pip install smartPID

Then load the library where you need it.

import smartPID

5.1 Position PID Controller

When you need to call the position PID controller, you can refer to the following code.The variable input_signal here refers to the feedback value of the measurement.

smartPID.position(input_signal)

You can use the following methods to set the PID parameters of the controller. (When we assume P = 0.2, I=0.5, D=0.1)

smartPID.set_PID(0.2,0.5,0.1)

You can use the following methods to set the setpoint of the PID controller. (When we assume setpoint = 5)

smartPID.set_set_point(5)

You can use the following methods to set the sampletime of the PID controller. (When we assume sampletime = 0.01)

smartPID.set_sampletime(0.01)

You can use the following methods to display the parameter of the PID controller.

smartPID.display_PIDvalue()

5.2 Incremental PID Controller

When you need to call the incremental PID controller, you can refer to the following code.The variable input_signal here refers to the feedback value of the measurement.

smartPID.incremental(input_signal)

You can use the following methods to set the PID parameters of the controller. (When we assume P = 0.2, I=0.5, D=0.1)

smartPID.set_PID(0.2,0.5,0.1)

You can use the following methods to set the setpoint of the PID controller. (When we assume setpoint = 5)

smartPID.set_set_point(5)

You can use the following methods to set the sampletime of the PID controller. (When we assume sampletime = 0.01)

smartPID.set_sampletime(0.01)

You can use the following methods to display the parameter of the PID controller.

smartPID.display_PIDvalue()

5.3 Single Neural PID Controller

When you need to call the single neural PID controller, you can refer to the following code.The variable input_signal here refers to the feedback value of the measurement.

smartPID.SNPID(input_signal)

You can use the following methods to set the learning rate of the whole single neural PID controller and each link. (When we assume the whole single neural PID learning rate is 0.03, the P link learning rate is 0.4, the I link learning rate is 0.2, the D link learning rate is 0.1)

smartPID.set_SNPID_LR(0.03,0.4,0.2,0.1)

You can use the following methods to set the initial values of the P link, I link and D link. (When we assume the initial value of the P link is 1.5, the initial value of the I link is 0.3, the initial value of the D link is 0.1)

smartPID.set_SNPID_IW(1.5,0.3,0.1)

You can use the following methods to set the setpoint of the single neural PID controller. (When we assume setpoint = 5)

smartPID.set_set_point(5)

You can use the following methods to set the sampletime of the single neural PID controller. (When we assume sampletime = 0.01)

smartPID.set_sampletime(0.01)

You can use the following methods to display the parameter of the single neural PID controller.

smartPID.display_SNPIDvalue()

5.4 Default parameters for the library

The default parameters of the position PID controller are as follows:

P=0.2

I=0.0

D=0.0

sampletime=0.01

The default parameters of the incremental PID controller are as follows:

P=0.2

I=0.0

D=0.0

sampletime=0.01

The default parameters of the single neural PID controller are as follows:

the whole single neural PID learning rate is 0.03

the P link learning rate is 0.1

the I link learning rate is 0.1

the D link learning rate is 0.1

the initial value of the P link is 0.1

the initial value of the I link is 0.1

the initial value of the D link is 0.1

sampletime=0.01