4 papers · 1 filter
Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
Ankur Kamboj, Biswadip Dey, Vaibhav Srivastava
We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approach co-learns a pH system model…
Multi-Robot Multitask Gaussian Process Estimation and Coverage
Lai Wei, Andrew McDonald, Vaibhav Srivastava
Coverage control is essential for the optimal deployment of agents to monitor or cover areas with sensory demands. While traditional coverage involves single-task robots, increasin…
Model-free Vehicle Rollover Prevention: A Data-driven Predictive Control Approach
Mohammad R. Hajidavalloo, Kaixiang Zhang, Vaibhav Srivastava +1
Vehicle rollovers pose a significant safety risk and account for a disproportionately high number of fatalities in road accidents. This paper addresses the challenge of rollover pr…
Online Reduced-Order Data-Enabled Predictive Control
Amin Vahidi-Moghaddam, Kaixiang Zhang, Xunyuan Yin +2
Data-enabled predictive control (DeePC) has garnered significant attention for its ability to achieve safe, data-driven optimal control without relying on explicit system models. T…