Extending iLQR method with control delay

02/16/2020

∙

Iterative linear quadradic regulator(iLQR) has become a benchmark method to deal with nonlinear stochastic optimal control problem. However, it does not apply to delay system. In this paper, we extend the iLQR theory and prove new theorem in case of input signal with fixed delay. Which could be beneficial for machine learning or optimal control application to real time robot or human assistive device.

READ FULL TEXT

Extending iLQR method with control delay

Deep learning method for solving stochastic optimal control problem via stochastic maximum principle

An Optimal Control View of Adversarial Machine Learning

Structured Hammerstein-Wiener Model Learning for Model Predictive Control

An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay

A Family of Iterative Gauss-Newton Shooting Methods for Nonlinear Optimal Control

Aggressive Online Control of a Quadrotor via Deep Network Representations of Optimality Principles

Optimal control and stablilization for linear continuous-time mean-field systems with delay

Extending iLQR method with control delay

Related Research

Deep learning method for solving stochastic optimal control problem via stochastic maximum principle

An Optimal Control View of Adversarial Machine Learning

Structured Hammerstein-Wiener Model Learning for Model Predictive Control

An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay

A Family of Iterative Gauss-Newton Shooting Methods for Nonlinear Optimal Control

Aggressive Online Control of a Quadrotor via Deep Network Representations of Optimality Principles

Optimal control and stablilization for linear continuous-time mean-field systems with delay