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Research PaperResearchia:202602.16014

A Data-Driven Algorithm for Model-Free Control Synthesis

Sean Bowerfind

Abstract

Presented is an algorithm to synthesize the optimal infinite-horizon LQR feedback controller for continuous-time systems. The algorithm does not require knowledge of the system dynamics but instead uses only a finite-length sampling of arbitrary input-output data. The algorithm is based on a constrained optimization problem that enforces a necessary condition on the dynamics of the optimal value function along any trajectory. In addition to calculating the standard LQR gain matrix, a feedforward...

Submitted: February 16, 2026Subjects: Mathematics; Mathematics

Description / Details

Presented is an algorithm to synthesize the optimal infinite-horizon LQR feedback controller for continuous-time systems. The algorithm does not require knowledge of the system dynamics but instead uses only a finite-length sampling of arbitrary input-output data. The algorithm is based on a constrained optimization problem that enforces a necessary condition on the dynamics of the optimal value function along any trajectory. In addition to calculating the standard LQR gain matrix, a feedforward gain can be found to implement a reference tracking controller. This paper presents a theoretical justification for the method and shows several examples, including a validation test on a real scale aircraft.


Source: arXiv:2602.13157v1 - http://arxiv.org/abs/2602.13157v1 PDF: https://arxiv.org/pdf/2602.13157v1 Original Link: http://arxiv.org/abs/2602.13157v1

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Date:
Feb 16, 2026
Topic:
Mathematics
Area:
Mathematics
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