Temporal Parallelization of Dynamic Programming and Linear Quadratic Control¶
Authors: Simo Sarkka, Angel F. Garcia-Fernandez
Published: 2021 (Journal Paper)
Source: IEEE Transactions on Automatic Control
Algorithm: LQR
arXiv: 2104.03186
DOI: 10.1109/TAC.2022.3147017
Summary¶
Abstract¶
This article proposes a general formulation for temporal parallelization of dynamic programming for optimal control problems. We derive the elements and associative operators to be able to use parallel scans to solve these problems with logarithmic time complexity rather than linear time complexity. We apply this methodology to problems with finite state and control spaces, linear quadratic tracking control problems, and to a class of nonlinear control problems. The computational benefits of the parallel methods are demonstrated via numerical simulations run on a graphics processing unit.