Papers
3
Total Citations
16
H-Index
2
About
Tushar Garg is a rising researcher in nonlinear control theory and multi-agent systems, with a focus on safety-critical and adaptive control without restrictive assumptions. His key contributions lie in developing novel controllers for Euler-Lagrange systems—which model mechanical plants like aircraft and quadrotors—using Barrier Lyapunov Functions to enforce user-defined safety constraints while reducing control effort. This work, his most cited paper (11 citations), addresses a fundamental challenge in real-world robotics and aerospace applications. Garg has also advanced distributed adaptive estimation for multi-agent systems, proposing algorithms that eliminate the need for persistence of excitation (PE)—a common but limiting requirement in classical adaptive control. His 2023 paper on this topic (3 citations) offers an online optimization perspective for continuous-time estimation. Most recently, his 2024 work on robust adaptive extremum-seeking control (2 citations) combines a proportional-integral-like parameter estimator with zeroth-order optimization, validated experimentally. By removing the PE condition, Garg’s research enables more practical, robust, and efficient control for complex systems, making his work highly relevant for students and engineers tackling real-world nonlinear control challenges.
Research Focus
Key Achievements
Top Papers
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