Model predictive control of non-holonomic systems: Beyond differential-drive vehicles

Abstract

Non-holonomic systems are of immense practical value and increasingly subject to automation. However, controlling them accurately, e.g., when parking vehicles, is challenging for automatic control methods, including model predictive control (MPC). Combining results from MPC theory and sub-Riemannian geometry in the form of homogeneous nilpotent system approximations, this paper proposes the first comprehensive, ready-to-apply design procedure for MPC controllers to steer controllable, driftless non-holonomic systems into given setpoints. It can be ascertained that the resulting controllers nominally asymptotically stabilize the setpoint for a large-enough prediction horizon. The design procedure is exemplarily applied to four systems, including the kinematic car and a differentially driven mobile robot with up to two trailers. The controllers use a non-quadratic cost function tailored to the non-holonomic kinematics. Novelly, it is proven that a quadratic cost employed in an otherwise similar controller is insufficient to reliably asymptotically stabilize the closed loop for all considered vehicles. Since quadratic costs are the conventional choice in control, this highlights the relevance of the findings. To the knowledge of the authors, it is the first time that MPC controllers of the proposed structure are formulated and applied to non-holonomic systems beyond very simple ones, in particular (partly) on hardware.