.png){kind=icon}
.png){kind=icon}
Return
LMI-Driven Reachability Analysis for Fuzzy Model-Based Nonlinear Systems Subject to Norm-Bounded Input Perturbations
.png){kind=icon}
PRE
AI
S
M
I
DOI：10.1109/LCSYS.2026.3659159.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this letter, we study the reachability analysis of fuzzy model-based nonlinear systems subject to norm-bounded input perturbations. While reachability analysis has been extensively studied in safety-critical control and verification, computing reachable sets for nonlinear systems remains challenging due to inherent computational and analytical complexities. To address this issue, we propose a Lyapunov-based reachability framework formulated via linear matrix inequalities (LMIs) within fuzzy modeling techniques. This framework represents a nonlinear system as a weighted summation of linear subsystems, while explicitly accounting for norm-bounded model approximation errors, enabling the effective application of linear control techniques. The proposed LMI-driven framework yields a Lyapunov function whose level sets provide an ellipsoidal over-approximated reachable set under both model approximation errors and norm-bounded perturbations. The effectiveness of the proposed framework is demonstrated using the attitude dynamics of a quadrotor unmanned aerial vehicle (UAV).
Keywords:
Safety
Approximation error
Perturbation methods
Computational modeling
Nonlinear dynamical systems
Reachability analysis
Lyapunov methods
Linear systems
Noise
Autonomous aerial vehicles
Linear matrix inequality
reachability
Lyapunov stability
fuzzy modeling
norm-bounded inputs
Journal
I
IF:
2
Papers:
94
Citations:
5.0K
Organization
Cited Papers