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Control-Oriented Identification for the Linear Quadratic Regulator: Technical Report by Anderson, Sean; Hespanha, João Pedro is a scholarly article available to read on EtoBox.

What is Control-Oriented Identification for the Linear Quadratic Regulator: Technical Report about?

Data-driven control benefits from rich datasets, but constructing such datasets becomes challenging when gathering data is limited. We consider an offline experiment design approach to gathering data where we design a control input to collect data that will most improve the performance of a feedback controller. We show how such a control-oriented approach can be used in a setting with linear dynamics and quadratic objective and, through design of a gradient estimator, solve the problem via stochastic gradient descent. We show our formulation numerically outperforms an A- and L-optimal experiment design approach as well as a robust dual control approach.

Author

Anderson, Sean; Hespanha, João Pedro

Published

2024

Language

EN