Safe Adaptive-Sampling Control via Robust M-Step Hold Model Predictive Control

TL;DR

This paper introduces a robust M-step hold model predictive control method that ensures safety and constraint satisfaction in adaptive-sampling control systems with variable control frequencies.

Contribution

It develops a new robust MPC framework with M-step hold extensions to guarantee safety under adaptive sampling and uncertain system models.

Findings

Ensures recursive feasibility using robust invariant sets.

Enables safe adaptive sampling through online M-step selection.

Validated in a cruise control example.

Abstract

In adaptive-sampling control, the control frequency can be adjusted during task execution. Ensuring that these changes do not jeopardize the safety of the system being controlled requires attention. We introduce robust M-step hold model predictive control (MPC) to address this. Our formulation provides robust constraint satisfaction for an uncertain discrete-time system model with a fixed sampling time subject to an adaptable multi-step input hold (referred to as M-step hold). We show how to ensure recursive feasibility of the MPC utilizing M-step hold extensions of robust invariant sets, and demonstrate how to enable safe adaptive-sampling control via the online selection of M. We evaluate the utility of the robust M-step hold MPC formulation in a cruise control example.