Efficiently Computable Constrained Optimal Feedback Controllers

Constrained optimal feedback controllers can be used to mitigate external perturbations and modeling errors in robot control. However, these controllers require extensive calculation which is one of their main limitations in the real-time implementation. Here we present two locally optimal feedback controllers which can be efficiently computed online in real- time. These controllers are applicable to systems with non- linear dynamics, nonlinear state and control dependent cost, and box constrained inputs. The proposed controllers differ from alternative feedback and re-computed feed-forward model predictive controllers which provide sub-optimal inputs and require significantly more online calculation in the real-time implementation. Theoretical arguments, a numerical simulation, and a robot control experiment substantiate our claims and show the applicability of the proposed efficiently computable constrained optimal feedback control method.