Reinforcement Learning and Fuzzy PID Control for Ball-on-plate Systems
Authors:
- 3 November 2022
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
Abstract
Ball-on-plate system (BPs) is a well-known two-dimensional balancing problem that many types of controllers were implemented. The Reinforcement Learning (RL) and Fuzzy PID controllers are proposed to improve the performance of time-domain response. The comparison of the controllers with PD controller shows the high robustness of disturbance rejection and the requirements of performance are satisfied. The application of RL becomes a solution with different characteristics from other traditional controllers, and the performance of Fuzzy PID is confirmed in the BPs control.Keywords
This publication has 6 references indexed in Scilit:
- Effect of Parameter Variation of Ball Balancer System Using PD and Fuzzy Control2022
- Nonlinear optimal control of the ball and plate dynamical systemAIP Conference Proceedings, 2022
- Observer integrated backstepping control for a ball and plate systemInternational Journal of Dynamics and Control, 2020
- Neural network-based PID compensation for nonlinear systems: ball-on-plate exampleInternational Journal of Dynamics and Control, 2018
- Virtual Laboratory of the Ball and Plate SystemIFAC-PapersOnLine, 2015
- Fuzzy PID controller: Design, performance evaluation, and stability analysisInformation Sciences, 2000