Extending iLQR method with control delay
This work addresses a specific bottleneck in optimal control for delay systems, which is incremental as it builds upon the existing iLQR framework.
The authors tackled the limitation of the iterative linear quadratic regulator (iLQR) method, which cannot handle systems with control delays, by extending its theory to include fixed input delays and proving new theorems, enabling applications in real-time robotics and human assistive devices.
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.