We study the problem of minimum-variance event-triggered output-feedback control of linear timeinvariant processes driven by white Gaussian noise. We show that the optimal event generation is separated from the controller configuration and can be determined by solving an optimal stopping problem. Then, for the case of integrator processes, we extend the Lebesgue sampling result of Aström and Bernhardsson in two directions: 1) we show that it applies to systems with measurement noise and limited control effort and 2) we prove that in the scalar case this control strategy is optimal, in a sense that no other causal event-triggered sampled-data controller with the same average sampling rate can outperform it.
|Number of pages||6|
|Journal||IEEE Control Systems Letters|
|State||Published - 2017|
Bibliographical noteFunding Information:
Manuscript received February 23, 2017; revised April 4, 2017; accepted May 1, 2017. Date of publication May 2, 2017; date of current version May 18, 2017. This work was supported by the Israel Science Foundation under Grant 361/15. Recommended by Senior Editor S. Tarbouriech. (Corresponding author: Leonid Mirkin.) A. Goldenshluger is with the Department of Statistics, University of Haifa, Haifa 31905, Israel (e-mail: firstname.lastname@example.org).
© 2017 Institute of Electrical and Electronics Engineers Inc. All rights reserved.
- Event-triggered control
- Minimum-variance optimization
- Optimal stopping
- Sampled-data systems
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization