Unified Multirate Control: From Low-Level Actuation to High-Level Planning

• Published in: IEEE transactions on automatic control Vol. 67; no. 12; pp. 6627 - 6640
• Main Authors: Rosolia, Ugo, Singletary, Andrew, Ames, Aaron D.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuation; Aerospace electronics; Computational modeling; Control barrier function (CBF); Controllers; Cost function; Decision making; hierarchical control; Markov processes; Mars exploration; multirate control; noisy observations; Nonlinear control; Nonlinear systems; partially observable; Planning; Predictive control; Specifications; Strategy; Temporal logic; Tracking control; Tracking errors; Trajectory
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2022.3184664

In this article, we present a hierarchical multirate control architecture for nonlinear autonomous systems operating in partially observable environments. Control objectives are expressed using syntactically co-safe linear temporal logic (LTL) specifications and the nonlinear system is subject to state and input constraints. At the highest level of abstraction, we model the system-environment interaction using a discrete mixed observable Markov decision process, where the environment states are partially observed. The high-level control policy is used to update the constraint sets and cost function of a model predictive controller (MPC) which plans a reference trajectory. Afterward, the MPC planned trajectory is fed to a low-level high-frequency tracking controller, which leverages control barrier functions to guarantee bounded tracking errors. Our strategy is based on model abstractions of increasing complexity and layers running at different frequencies. We show that the proposed hierarchical multirate control architecture maximizes the probability of satisfying the high-level specifications, while guaranteeing state and input constraint satisfaction. Finally, we tested the proposed strategy in simulations and experiments on examples inspired by the Mars exploration mission, where only partial environment observations are available.