Jiaxuan Song
Papers
1
Total Citations
6
H-Index
1
About
Jiaxuan Song is a rising researcher in nonlinear control theory, with a focus on fixed-time stability and adaptive neural control for uncertain dynamical systems. Their most-cited work, "Nonsingular fixed‐time adaptive neural terminal sliding mode control for a class of uncertain second‐order nonlinear systems" (2024, 6 citations), introduces a novel fast fixed-time stable autonomous system featuring a switched nonlinear term. This contribution addresses key challenges in second-order uncertain nonlinear systems by eliminating singularities in terminal sliding mode control while ensuring convergence within a bounded time independent of initial conditions. Song's approach integrates adaptive neural networks to handle system uncertainties without prior knowledge of bounds, advancing the practical applicability of fixed-time control in robotics and aerospace. Though early in their career, their work has already garnered attention for its theoretical rigor and potential for real-world implementation. By proposing a more efficient convergence framework than traditional fixed-time methods, Song is establishing themselves as an innovator in robust nonlinear control, with future work likely to extend these principles to higher-order systems and multi-agent coordination.
Research Focus
Key Achievements
Top Papers
- 1