# Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Reinforcement-Learning

**Repository Path**: IMdean/Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Reinforcement-Learning

## Basic Information

- **Project Name**: Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Reinforcement-Learning
- **Description**: 神经网络用于调整PID
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-25
- **Last Updated**: 2021-11-25

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Function-Approximation-and-Adaptive-PID-Gain-Tuning-using-Neural-Networks-and-Actor-Critic-algorithm
System Identification and Self-Tuning PID Control using NN and reinforcement learning

Notes --->

PID_FA_NN.m : 

    this file is Fucntion approximation using Neural Networks with Adaptive PID Gains
    
    You can read the attached "PID Neural Networks.pdf" file for learning algorithm and structures.

![PID_FA_NN](https://user-images.githubusercontent.com/60617560/129597840-e8d9f399-4de6-4a1a-8218-b4fd27fd5570.png)

![PID_gains](https://user-images.githubusercontent.com/60617560/129597930-453bcfa4-9962-4000-905a-179b3a898e61.png)

FA_A2C.m :

    Function Approximation using Actor-Critic Algorithm
![FA_A2C](https://user-images.githubusercontent.com/60617560/129596768-e3680e6c-bc19-4833-b5cb-73681c8fb1ef.png)

If you want to change the dynamic system, Please just change the function "NonLinDynamic" in .m file.