Approximately Supermodular Scheduling Subject to Matroid Constraints

Control scheduling refers to the problem of assigning agents or actuators to act upon a dynamical system at specific times so as to minimize a quadratic control cost, such as the objectives of the linear-quadratic-Gaussian (LQG) or linear quadratic regulator problems. When budget or operational cons...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 67; no. 3; pp. 1384 - 1396
Main Authors Chamon, Luiz F. O., Amice, Alexandre, Ribeiro, Alejandro
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Control scheduling refers to the problem of assigning agents or actuators to act upon a dynamical system at specific times so as to minimize a quadratic control cost, such as the objectives of the linear-quadratic-Gaussian (LQG) or linear quadratic regulator problems. When budget or operational constraints are imposed on the schedule, this problem is in general NP-hard and its solution can therefore only be approximated even for moderately sized systems. The quality of this approximation depends on the structure of both the constraints and the objective. This article shows that greedy control scheduling is near-optimal when the constraints can be written as an intersection of matroids, algebraic structures that encode requirements such as limits on the number of agents deployed per time slot, total number of actuator uses, and duty cycle restrictions. To do so, it proves that the LQG cost function is <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>-supermodular and provides new <inline-formula><tex-math notation="LaTeX">\alpha /(\alpha + P)</tex-math></inline-formula>-optimality certificates for the greedy minimization of such functions over an intersection of <inline-formula><tex-math notation="LaTeX">P</tex-math></inline-formula> matroids. These certificates are shown to approach the <inline-formula><tex-math notation="LaTeX">1/(1+P)</tex-math></inline-formula> guarantee of supermodular functions in relevant settings. These results support the use of greedy algorithms in nonsupermodular quadratic control problems as opposed to typical heuristics such as convex relaxations and surrogate figures of merit, e.g., the <inline-formula><tex-math notation="LaTeX">\log \det</tex-math></inline-formula> of the controllability Gramian.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2021.3071024