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Scalable Robust Adaptive Control from the System Level Perspective

Ho, Dimitar and Doyle, John C. (2019) Scalable Robust Adaptive Control from the System Level Perspective. In: 2019 American Control Conference (ACC). IEEE , Piscataway, NJ, pp. 3683-3688. ISBN 978-1-5386-7926-5.

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We will present a new general framework for robust and adaptive control that allows for distributed and scalable learning and control of large systems of interconnected linear subsystems. The control method is demonstrated for a linear time-invariant system with bounded parameter uncertainties, disturbances and noise. The presented scheme continuously collects measurements to reduce the uncertainty about the system parameters and adapts dynamic robust controllers online in a stable and performance-improving way. A key enabler for our approach is choosing a time-varying dynamic controller implementation, inspired by recent work on System Level Synthesis [1]. We leverage a new robustness result for this implementation to propose a general robust adaptive control algorithm. In particular, the algorithm allows us to impose communication and delay constraints on the controller implementation and is formulated as a sequence of robust optimization problems that can be solved in a distributed manner. The proposed control methodology performs particularly well when the interconnection between systems is sparse and the dynamics of local regions of subsystems depend only on a small number of parameters. As we will show on a five-dimensional exemplary chain-system, the algorithm can utilize system structure to efficiently learn and control the entire system while respecting communication and implementation constraints. Moreover, although current theoretical results require the assumption of small initial uncertainties to guarantee robustness, we will present simulations that show good closed-loop performance even in the case of large uncertainties, which suggests that this assumption is not critical for the presented technique and future work will focus on providing less conservative guarantees.

Item Type:Book Section
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Doyle, John C.0000-0002-1828-2486
Additional Information:© 2019 AACC.
Record Number:CaltechAUTHORS:20190617-112254520
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Official Citation:D. Ho and J. C. Doyle, "Scalable Robust Adaptive Control from the System Level Perspective," 2019 American Control Conference (ACC), Philadelphia, PA, USA, 2019, pp. 3683-3688. URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96471
Deposited By: Tony Diaz
Deposited On:17 Jun 2019 18:31
Last Modified:03 Oct 2019 21:22

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