5 papers
Performance Index Shaping for Closed-loop Optimal Control
Ayush Rai, Shaoshuai Mou, Brian D. O. Anderson
The design of the performance index, also referred to as cost or reward shaping, is central to both optimal control and reinforcement learning, as it directly determines the behavi…
Distributed Koopman Learning with Incomplete Measurements
Wenjian Hao, Lili Wang, Ayush Rai +1
Koopman operator theory has emerged as a powerful tool for system identification, particularly for approximating nonlinear time-invariant systems (NTIS). This paper considers a net…
Neighboring Extremal Optimal Control Theory for Parameter-Dependent Closed-loop Laws
Ayush Rai, Shaoshuai Mou, Brian D. O. Anderson
This study introduces an approach to obtain a neighboring extremal optimal control (NEOC) solution for a closed-loop optimal control problem, applicable to a wide array of nonlinea…
Distributed Optimization via Kernelized Multi-armed Bandits
Ayush Rai, Shaoshuai Mou
Multi-armed bandit algorithms provide solutions for sequential decision-making where learning takes place by interacting with the environment. In this work, we model a distributed…
Safe Region Multi-Agent Formation Control With Velocity Tracking
Ayush Rai, Shaoshuai Mou
This paper provides a solution to the problem of safe region formation control with reference velocity tracking for a second-order multi-agent system without velocity measurements.…