For sampled-data control systems, where a continuous-time plant is under digital control, one of the most important design parameter is the sample rate/period. Higher sample rate typically is associated with the need of high performance components and processors that results in higher system cost. In this paper, we propose an approach to determine the slowest sample rate for a sampled-data control system that will achieve the desired performance and robustness specifications. An optimization problem can be formulated using lifting technique to parameterize sample period for a sampled-data control system. The utility of the proposed approach is numerically verified through the control systems design of the media advance system of an inkjet printer.
Skip Nav Destination
ASME 2009 Dynamic Systems and Control Conference
October 12–14, 2009
Hollywood, California, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4892-0
PROCEEDINGS PAPER
Determining Maximum Sample Period Under Performance Constraints for Sampled-Data Control Systems
Jie Ma,
Jie Ma
Harbin Institute of Technology, Harbin, China
Search for other works by this author on:
George T.-C. Chiu
George T.-C. Chiu
Purdue University, West Lafayette, IN
Search for other works by this author on:
Jie Ma
Harbin Institute of Technology, Harbin, China
George T.-C. Chiu
Purdue University, West Lafayette, IN
Paper No:
DSCC2009-2747, pp. 437-443; 7 pages
Published Online:
September 16, 2010
Citation
Ma, J, & Chiu, GT. "Determining Maximum Sample Period Under Performance Constraints for Sampled-Data Control Systems." Proceedings of the ASME 2009 Dynamic Systems and Control Conference. ASME 2009 Dynamic Systems and Control Conference, Volume 1. Hollywood, California, USA. October 12–14, 2009. pp. 437-443. ASME. https://doi.org/10.1115/DSCC2009-2747
Download citation file:
4
Views
Related Proceedings Papers
Related Articles
An Improved Reactive Power MRAS Speed Estimator With Optimization for a Hybrid Electric Vehicles Application
J. Dyn. Sys., Meas., Control (June,2018)
Sequential Design Process for Screening and Optimization of Robustness and Reliability Based on Finite Element Analysis and Meta-Modeling
J. Comput. Inf. Sci. Eng (August,2022)
Modeling and Cascade Control of a Pneumatic Positioning System
J. Dyn. Sys., Meas., Control (June,2022)
Related Chapters
Getting Ready for Production
Total Quality Development: A Step by Step Guide to World Class Concurrent Engineering
The Impact of Plant Economics on the Design of Industrial Energy Systems
Industrial Energy Systems
S/N (Signal-to-Noise) Ratios for Static Characteristics and the Robustness Optimization Procedure
Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications