SYSYApr 9

Linear Feedback Controller for Homogeneous Polynomial Systems

arXiv:2604.087212.7h-index: 7
Predicted impact top 64% in SY · last 90 daysOriginality Incremental advance
AI Analysis

For control theorists working on polynomial systems, this offers a computationally efficient alternative to local linearization or SOS methods, though limited to systems with ODECO structure.

This paper proposes a structure-preserving linear feedback controller for homogeneous polynomial systems with orthogonally decomposable tensor dynamics, enabling closed-form trajectory expressions and sharp region-of-attraction estimates. The approach avoids conservative Lyapunov/SOS methods and provides explicit convergence thresholds.

This paper studies stabilization and its corresponding closed-loop region-of-attraction (ROA) for homogeneous polynomial dynamical systems whose nonlinear term admits an orthogonally decomposable (ODECO) tensor representation. While recent tensor-based results provide explicit solutions and sharp global characterizations for open-loop ODECO systems, closed-loop synthesis and computable ROA estimates are still often dominated by local linearization or Lyapunov/SOS (sum of squares) methods, which can be conservative and computationally demanding. We propose a structure-preserving linear feedback design that shares the ODECO eigenbasis of the system's tensor, thereby enabling closed-form trajectory expressions, explicit convergence/escape thresholds, and sharp ROA characterizations. Under mild conditions, we further derive robustness/ISS-type bounds for bounded disturbances. Numerical examples validate the theoretical results.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes