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Behavioral Feedback for Optimal LQG Control

Makdah, AAA and Krishnan, V and Katewa, V and Pasqualetti, F (2022) Behavioral Feedback for Optimal LQG Control. In: 61st IEEE Conference on Decision and Control, CDC 2022, 6 - 9 December 2022, Cancun, pp. 4660-4666.

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Official URL: https://doi.org/10.1109/CDC51059.2022.9992774


In this work, we revisit the Linear Quadratic Gaussian (LQG) optimal control problem from a behavioral perspective. Motivated by the suitability of behavioral models for data-driven control, we begin with a reformulation of the LQG problem in the space of input-output behaviors and obtain a complete characterization of the optimal solutions. In particular, we show that the optimal LQG controller can be expressed as a static behavioral-feedback gain, thereby eliminating the need for dynamic state estimation characteristic of state space methods. The static form of the optimal LQG gain also makes it amenable to its computation by gradient descent, which we investigate via numerical experiments. Furthermore, we highlight the advantage of this approach in the data-driven control setting of learning the optimal LQG controller from expert demonstrations. © 2022 IEEE.

Item Type: Conference Paper
Publication: Proceedings of the IEEE Conference on Decision and Control
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to the Authors.
Keywords: Controllers; Feedback; Gradient methods; Optimal control systems, Behavioral feedback; Behavioral model; Data-driven control; Feedback gain; Input/output behaviors; Linear quadratic Gaussian; Linear quadratic Gaussian control; Linear Quadratic Gaussian controllers; Optimal control problem; Optimal solutions, State space methods
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 16 Feb 2023 05:41
Last Modified: 16 Feb 2023 05:41
URI: https://eprints.iisc.ac.in/id/eprint/80333

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