Search Results for author:
Found 11 papers, 2 papers with code
On the Predictive Capability of Dynamic Mode Decomposition for Nonlinear Periodic Systems with Focus on Orbital Mechanics
This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics.
An Information-State Based Approach to Linear Time Varying System Identification and Control
This paper considers the problem of system identification for linear time varying systems.
Optimal Control of Material Micro-Structures
In this paper, we consider the optimal control of material micro-structures.
On the Convergence of Reinforcement Learning in Nonlinear Continuous State Space Problems
We consider the problem of Reinforcement Learning for nonlinear stochastic dynamical systems.
On the Feedback Law in Stochastic Optimal Nonlinear Control
We consider the problem of nonlinear stochastic optimal control.
On the Search for Feedback in Reinforcement Learning
The problem of Reinforcement Learning (RL) in an unknown nonlinear dynamical system is equivalent to the search for an optimal feedback law utilizing the simulations/ rollouts of the dynamical system.
Experiments with Tractable Feedback in Robotic Planning under Uncertainty: Insights over a wide range of noise regimes (Extended Report)
We consider the problem of robotic planning under uncertainty.
Optimization and Control Robotics Systems and Control Systems and Control
Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems
This paper proposes a novel decoupled data-based control (D2C) algorithm that addresses this problem using a decoupled, `open loop - closed loop', approach.
A Separation-Based Design to Data-Driven Control for Large-Scale Partially Observed Systems
This paper studies the partially observed stochastic optimal control problem for systems with state dynamics governed by Partial Differential Equations (PDEs) that leads to an extremely large problem.
Stochastic Feedback Control of Systems with Unknown Nonlinear Dynamics
This paper studies the stochastic optimal control problem for systems with unknown dynamics.
Belief Space Planning Simplified: Trajectory-Optimized LQG (T-LQG) (Extended Report)
Planning under motion and observation uncertainties requires solution of a stochastic control problem in the space of feedback policies.
Robotics Optimization and Control
