10 citations · 14 across the 5 of their papers we have counts for
6 papers
Port-Hamiltonian Koopman Operator Synthesis for Mechanical Systems
Rajpal Singh, Aditya Singh, Jishnu Keshavan
Finite-dimensional Koopman models enable efficient linear prediction and control of nonlinear robotic systems. However, models learned purely from trajectory data may violate the e…
SACK : Safe Active Continual Koopman Learning for Uncertain Systems with Contractive Guarantees
Chandan Kumar Sah, Rajpal Singh, Jishnu Keshavan
Koopman operator theory provides a powerful framework for representing nonlinear dynamics through a linear operator acting on lifted observables, enabling the use of linear control…
Deep Robust Koopman Learning from Noisy Data
Aditya Singh, Rajpal Singh, Jishnu Keshavan
Koopman operator theory has emerged as a leading data-driven approach that relies on a judicious choice of observable functions to realize global linear representations of nonlinea…
Generalized Momenta-Based Koopman Formalism for Robust Control of Euler-Lagrangian Systems
Rajpal Singh, Aditya Singh, Chidre Shravista Kashyap +1
This paper presents a novel Koopman operator formulation for Euler Lagrangian dynamics that employs an implicit generalized momentum-based state space representation, which decoupl…
Adaptive Koopman Embedding for Robust Control of Complex Nonlinear Dynamical Systems
Rajpal Singh, Chandan Kumar Sah, Jishnu Keshavan
The discovery of linear embedding is the key to the synthesis of linear control techniques for nonlinear systems. In recent years, while Koopman operator theory has become a promin…
A Collision Cone Approach for Control Barrier Functions
Manan Tayal, Bhavya Giri Goswami, Karthik Rajgopal +5
This work presents a unified approach for collision avoidance using Collision-Cone Control Barrier Functions (CBFs) in both ground (UGV) and aerial (UAV) unmanned vehicles. We prop…