DocumentCode
22043
Title
On the Optimality of Certainty Equivalence for Event-Triggered Control Systems
Author
Molin, Adam ; Hirche, Sandra
Author_Institution
Inst. of Autom. Control Eng., Tech. Univ. Munchen, München, Germany
Volume
58
Issue
2
fYear
2013
fDate
Feb. 2013
Firstpage
470
Lastpage
474
Abstract
Digital control design is commonly constrained to time-triggered control systems with periodic sampling. The emergence of more and more complex and distributed systems urges the development of advanced triggering schemes that utilize communication, computation, and energy resources more efficiently. This technical note addresses the question whether certainty equivalence is optimal for an event-triggered control system with resource constraints. The problem setting is an extension of the stochastic linear quadratic system framework, where the joint design of the control law and the event-triggering law minimizing a common objective is considered. Three differing variants are studied that reflect the resource constraints: a penalty term to acquire the resource, a limitation on the number of resource acquisitions, and a constraint on the average number of resource acquisitions. By reformulating the underlying optimization problem, a characterization of the optimal control law is possible. This characterization shows that the certainty equivalence controller is optimal for all three optimization problems.
Keywords
control system synthesis; digital control; linear quadratic control; optimisation; sampling methods; stochastic systems; certainty equivalence controller; certainty equivalence optimality; digital control design; energy resources; event-triggered control systems; event-triggering law; optimal control law; optimization problems; periodic sampling; resource acquisitions; stochastic linear quadratic system framework; time-triggered control systems; Conferences; Optimal control; Optimization; Process control; Random variables; Stochastic processes; Certainty equivalence; event-triggered control; networked control systems; resource-aware control; stochastic optimal control;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2012.2206719
Filename
6228515
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