T-PFC: A Trajectory-Optimized Perturbation Feedback Control Approach | Academic Article individual record
abstract

© 2019 IEEE. Traditional stochastic optimal control methods that attempt to obtain an optimal feedback policy for nonlinear systems are computationally intractable. In this letter, we derive a decoupling principle between the open-loop plan, and the closed-loop feedback gains, which leads to a deterministic perturbation feedback control based solution to fully observable stochastic optimal control problems, that is near-optimal. Extensive numerical simulations validate the theory, revealing a wide range of applicability, coping with medium levels of noise. The performance is compared against a set of baselines in several difficult robotic planning and control examples that show near identical performance to nonlinear model predictive control while requiring much lesser computational effort.

author list (cited authors)
Parunandi, K. S., & Chakravorty, S.
publication date
2019
citation count

0