Sparse State-Space Realizations of Linear Controllers

Fuente: arXiv
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Main Authors: Du, Yaozhi, Li, Jing Shuang
Format: Preprint
Published: 2026
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author Du, Yaozhi
Li, Jing Shuang
author_facet Du, Yaozhi
Li, Jing Shuang
contents This paper provides a novel approach for finding sparse state-space realizations of linear systems (e.g., controllers). Sparse controllers are commonly used in distributed control, where a controller is synthesized with some sparsity penalty. Here, motivated by a modeling problem in sensorimotor neuroscience, we study a complementary question: given a linear time-invariant system (e.g., controller) in transfer function form and a desired sparsity pattern, can we find a suitably sparse state-space realization for the transfer function? This problem is highly nonconvex, but we propose an exact method to solve it. We show that the problem reduces to finding an appropriate similarity transform from the modal realization, which in turn reduces to solving a system of multivariate polynomial equations. Finally, we leverage tools from algebraic geometry (namely, the Gröbner basis) to solve this problem exactly. We provide algorithms to find real- and complex-valued sparse realizations and demonstrate their efficacy on several examples.
format Preprint
id arxiv_https___arxiv_org_abs_2603_28754
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Sparse State-Space Realizations of Linear Controllers
Du, Yaozhi
Li, Jing Shuang
Systems and Control
This paper provides a novel approach for finding sparse state-space realizations of linear systems (e.g., controllers). Sparse controllers are commonly used in distributed control, where a controller is synthesized with some sparsity penalty. Here, motivated by a modeling problem in sensorimotor neuroscience, we study a complementary question: given a linear time-invariant system (e.g., controller) in transfer function form and a desired sparsity pattern, can we find a suitably sparse state-space realization for the transfer function? This problem is highly nonconvex, but we propose an exact method to solve it. We show that the problem reduces to finding an appropriate similarity transform from the modal realization, which in turn reduces to solving a system of multivariate polynomial equations. Finally, we leverage tools from algebraic geometry (namely, the Gröbner basis) to solve this problem exactly. We provide algorithms to find real- and complex-valued sparse realizations and demonstrate their efficacy on several examples.
title Sparse State-Space Realizations of Linear Controllers
topic Systems and Control
url https://arxiv.org/abs/2603.28754