As the technology progresses, the control tasks are getting increasingly complex. Employing the targeted algorithms for such control tasks and manually tuning them by trial and error (as in case of PID), is a cumbersome and lengthy process. Additionally, methods such as PID are designed for linear systems, however, all the real world control tasks are inherently non-linear in nature. With such complex tasks, using the conventional linear control methods approximates the nonlinear system to a linear model and in effect required performance is difficult to achieve.

The new advances in the field of AI have presented us with techniques which may help replace the traditional control algorithms. Use of AI may allow us to achieve a higher quality of control on the nonlinear process, with minimum human interaction. Thus eliminating the requirement for a skilled person to perform meager tasks of tuning control algorithms with trial and error.

Here we consider a simple case study of a beam balancer, where the controller is used for balancing a beam on a pivot to stabilize the ball at the center of the beam. We aim to implement a Reinforcement Learning based controller as an alternative to PID. We analyze the quality and compare the performance of PID-based controller vs. a RL-based controller to better understand the suitability for real-world control tasks.

 
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Outline/Structure of the Case Study

Explanation about PID and its domain of use

Problems with PID tuning

Introduction to Reinforcement Learning

Case Study :

Discussion about ball on a beam balancer model

Mathematical modeling using Neural Network

Tuning of PID for the model

Implementing the RL algorithm for the system

Comparative Analysis of both control algorithms

Learning Outcome

  1. Understand the overview of basic concepts of Reinforcement learning
  2. Get an overview of PID and tuning of PID parameters and problems associated with it
  3. Gain an insight into performance comparison of PID vs RL-based controller

Target Audience

People working in the domain of Robotics and AI, Control Engineering

Prerequisites for Attendees

Basics of Control Theory- PID

schedule Submitted 1 month ago

Public Feedback

comment Suggest improvements to the Speaker
  • Dr. Vikas Agrawal
    By Dr. Vikas Agrawal  ~  3 weeks ago
    reply Reply

    Dear Rahee: Given that both RL and PID are based on feedback, will you discuss the details of the math as well. I would love to see that.

    • Rahee Walambe
      By Rahee Walambe  ~  1 month ago
      reply Reply

      Dear Dr. Vikas,

      Thank you for your comment. Yes, we will be discussing the math behind both PID as well as RL, pertaining to the model of the system under discussion. I will add this in the proposal description.

      Rahee


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