One of the most popular trajectory-tracking controllers used in industry is the PID controller. The PID controller utilizes three types of gains and the tracking error in order to provide a control gain to a system. The PID gains may be tuned manually or using a number of different techniques. Under most operating conditions, only one set of PID gains are used. However, techniques exist to compensate for dynamic systems such as gain scheduling or basic time-varying functions. In this paper, an adaptive PID controller is presented based on Bayesian theory. The interacting multiple model (IMM) method, which utilizes Bayes’ theorem and likelihood functions, is implemented on the PID controller to present an adaptive control strategy. The strategy is applied to a simulated electromechanical system, and the results of the proposed controller are compared with the standard PID method. Future work is also considered.
Skip Nav Destination
Close
Sign In or Register for Account
ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5828-8
PROCEEDINGS PAPER
An Adaptive PID Controller Based on Bayesian Theory
S. Andrew Gadsden
S. Andrew Gadsden
University of Guelph, Guelph, ON, Canada
Search for other works by this author on:
S. Andrew Gadsden
University of Guelph, Guelph, ON, Canada
Paper No:
DSCC2017-5340, V002T12A005; 7 pages
Published Online:
November 14, 2017
Citation
Gadsden, SA. "An Adaptive PID Controller Based on Bayesian Theory." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. Tysons, Virginia, USA. October 11–13, 2017. V002T12A005. ASME. https://doi.org/10.1115/DSCC2017-5340
Download citation file:
- Ris (Zotero)
- Reference Manager
- EasyBib
- Bookends
- Mendeley
- Papers
- EndNote
- RefWorks
- BibTex
- ProCite
- Medlars
Close
Sign In
41
Views
0
Citations
Related Proceedings Papers
Related Articles
Least Squares Adaptive Control for Trajectory Following Robots
J. Dyn. Sys., Meas., Control (June,1987)
Desired Compensation Adaptive Robust Control
J. Dyn. Sys., Meas., Control (November,2009)
State Feedback Gain Scheduling for Linear Systems With Time-Varying Parameters
J. Dyn. Sys., Meas., Control (June,2006)
Related Chapters
New H∞ Controllers Design for Networked Control System with Disturbance Based on Asynchronous Dynamical System
International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)
Dynamic Positioning of Ships Using Direct Model Reference Adaptive Control
Intelligent Engineering Systems through Artificial Neural Networks Volume 18
Adaptive Control and Stability Analysis of Genetic Networks with SUM Regulation
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16