On moment relaxations for linear state feedback controller synthesis with non-convex quadratic costs and constraints
<|reference_start|>On moment relaxations for linear state feedback controller synthesis with non-convex quadratic costs and constraints: We present a simple and effective way to account for non-convex costs and constraints~in~state feedback synthesis, and an interpretation for the variables in which state feedback synthesis is typically convex. We achieve this by deriving the controller design using moment matrices of state and input. It turns out that this approach allows the consideration of non-convex constraints by relaxing them as expectation constraints, and that the variables in which state feedback synthesis is typically convexified can be identified with blocks of these moment matrices.<|reference_end|>
@article{gramlich2024on,
    title={On moment relaxations for linear state feedback controller synthesis
  with non-convex quadratic costs and constraints},
    author={Dennis Gramlich, Sheng Gao, Hao Zhang, Carsten W. Scherer and
  Christian Ebenbauer},
    journal={arXiv preprint arXiv:2403.15228},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.15228},
    primaryClass={math.OC cs.SY eess.SY}
}