System level synthesis: A tutorial

Doyle, John C.; Matni, Nikolai; Wang, Yuh-Shyang; Anderson, James; Low, Steven H.

doi:10.1109/cdc.2017.8264074

Cited by 20 publications

(40 citation statements)

References 25 publications

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“…This paper summarizes, and in some places extends, our recent theoretical and computational contributions [43,44,45,46,47,48,49,50,51,52,53,54,55,19] to the area of constrained optimal and robust controller synthesis. In particular, we…”

Section: Main Contributionsmentioning

confidence: 71%

System level synthesis

Anderson

Doyle

Low

et al. 2019

Annual Reviews in Control

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154

239

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Section: Main Contributionsmentioning

confidence: 71%

System level synthesis

Anderson

Doyle

Low

et al. 2019

Annual Reviews in Control

Self Cite

154

239

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“…To synthesize the state-feedback closed-loop controller for the system described in (1), SLS introduces the system response {Φ x , Φ u } transfer matrices. The system response is the closed-loop mapping from disturbance d x to state x and control action u, under the feedback policy u = Kx.…”

Section: A System Level Synthesis (Sls) -An Overviewmentioning

confidence: 99%

“…Φu [1] Φu [2] Φu [3] Φu [4] Deploying a synthesized solution to the centralized architecture is simple: We take the spectral components Φ u [τ ] of Φ u from τ = 1, 2, . .…”

Section: B Centralized Architecturementioning

confidence: 99%

“…Synthesizing an optimal controller for a cyber-physical system is, in general, a daunting task. Recently, a framework named system level synthesis (SLS) was proposed to facilitate distributed controller synthesis for large-scale (networked) systems [1]- [3]. Instead of designing the controller itself, SLS directly synthesizes desired closed-loop system responses subject to system level constraints, such as localization constraints [4] and state and input constraints [5].…”

Section: Introductionmentioning

confidence: 99%

“…SLS control block diagram derived in[1]. The signals of interest are δ = x −x, u = zΦu, and −x = I − zΦx.…”

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confidence: 99%

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Deployment Architectures for Cyber-Physical Control Systems

Tseng

Anderson

2020

2020 American Control Conference (ACC)

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We consider the problem of how to deploy a controller to a (networked) cyber-physical system (CPS). Controlling a CPS is an involved task, and synthesizing a controller to respect sensing, actuation, and communication constraints is only part of the challenge. In addition to controller synthesis, one should also consider how the controller will work in the CPS. Put another way, the cyber layer and its interaction with the physical layer need to be taken into account. In this work, we aim to bridge the gap between theoretical controller synthesis and practical CPS deployment. We adopt the system level synthesis (SLS) framework to synthesize a state-feedback controller and provide a deployment architecture for the standard SLS controller. Furthermore, we derive a new controller realization for open-loop stable systems and introduce four different architectures for deployment, ranging from fully centralized to fully distributed. Finally, we compare the trade-offs among them in terms of robustness, memory, computation, and communication overhead. Notation and Terminology: Let RH ∞ denote the set of stable rational proper transfer matrices, and z −1 RH ∞ ⊂ RH ∞ be the subset of strictly proper stable transfer matrices. Lower-and upper-case letters (such as x and A) denote vectors and matrices respectively, while bold lower-and upper-case characters and symbols (such as u and Φ u) are reserved for signals and transfer matrices. Let A ij be the entry of A at the i th row and j th column. We define A i as the i th row and A j the j th column of A. We use Φ u [τ ] to denote the τ th spectral element of a transfer function Φ u , i.e., Φ u = ∞ τ =0 z −τ Φ u [τ ]. We briefly summarize below the major terminology: • Controller model: a (linear) map from the state vector to the control action. • Realization: a control block diagram/state space dynamics based on some controller model. • Architecture: a cyber-physical system structure built from basic components. • Synthesize: derive a controller model (and some realization). • Deploy/Implement: map a controller model (through a realization) to an architecture.

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Introduction

Bavafa-Toosi¹

2019

Introduction to Linear Control Systems

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System level synthesis: A tutorial

Cited by 20 publications

References 25 publications

System level synthesis

System level synthesis

Deployment Architectures for Cyber-Physical Control Systems

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