Can AI replace Traditional Control Algorithms?
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.
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
- Understand the overview of basic concepts of Reinforcement learning
- Get an overview of PID and tuning of PID parameters and problems associated with it
- Gain an insight into performance comparison of PID vs RL-based controller
People working in the domain of Robotics and AI, Control Engineering
Prerequisites for Attendees
Basics of Control Theory- PID
schedule Submitted 3 months ago
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