2 citations · 4 across the 10 of their papers we have counts for
13 papers
Decentralized Bi-Level Optimization for Cooperative Orbital Transportation of a Rigid Payload
Sidhdharth D. Sikka, Revathy Ravuri, Hei Yin Jowett Chan +2
The rapid growth of the space economy, alongside increasing orbital congestion and debris, is driving demand for reliable on-orbit transportation of large and non-cooperative objec…
Stability Transfer for Autonomous Systems via Higher-Order Taylor-Truncated Lyapunov Certificates
Jose D. Hoyos, Zehui Lu, Shaoshuai Mou
We develop analytical sufficient conditions for certifying the local asymptotic stability of nonlinear autonomous systems based on Lyapunov functions derived from their finite-orde…
Stress-Sharing for Decentralized Fault Repair in Modular Spacecraft
Sidhdharth D. Sikka, Yue Shen, Shaoshuai Mou
Structural damage in modular spacecraft can disrupt mechanical and communication connectivity, reducing system capability. Existing approaches rely on redundancy or preplanned reco…
Safe Online Control-Informed Learning
Tianyu Zhou, Zihao Liang, Zehui Lu +1
This paper proposes a Safe Online Control-Informed Learning framework for safety-critical autonomous systems. The framework unifies optimal control, parameter estimation, and safet…
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…
Machine Learning-Driven Prediction of Lithium-Ion Battery Power Capability for eVTOL Aircraft
Hao Tu, Yebin Wang, Shaoshuai Mou +1
Electric vertical take-off and landing (eVTOL) aircraft have emerged as a promising solution to transform urban transportation. They present a few technical challenges for battery…
A Control-Barrier-Function-Based Algorithm for Policy Adaptation in Reinforcement Learning
Wenjian Hao, Zehui Lu, Nicolas Miguel +1
This paper considers the problem of adapting a predesigned policy, represented by a parameterized function class, from a solution that minimizes a given original cost function to a…
Trajectory Prediction via Bayesian Intention Inference under Unknown Goals and Kinematics
Shunan Yin, Zehui Lu, Shaoshuai Mou
This work introduces an adaptive Bayesian algorithm for real-time trajectory prediction via intention inference, where a target's intentions and motion characteristics are unknown…
Reward-Based Collision-Free Algorithm for Trajectory Planning of Autonomous Robots
Jose D. Hoyos, Tianyu Zhou, Zehui Lu +1
This paper proposes a novel mission planning algorithm for autonomous robots that selects an optimal waypoint sequence from a predefined set to maximize total reward while satisfyi…
Online Control-Informed Learning
Zihao Liang, Tianyu Zhou, Zehui Lu +1
This paper proposes an Online Control-Informed Learning (OCIL) framework, which employs the well-established optimal control and state estimation techniques in the field of control…
Distributed Optimization under Edge Agreement with Application in Battery Network Management
Zehui Lu, Shaoshuai Mou
This paper investigates a distributed optimization problem under edge agreements, where each agent in the network is also subject to local convex constraints. Generalized from the…
Integrated Optimal Fast Charging and Active Thermal Management of Lithium-Ion Batteries in Extreme Ambient Temperatures
Zehui Lu, Hao Tu, Huazhen Fang +2
This paper presents an integrated control strategy for optimal fast charging and active thermal management of Lithium-ion batteries in extreme ambient temperatures, striking a bala…
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…