Comparing Feedback Linearization and Adaptive Backstepping Control for Airborne Orientation of Agile Ground Robots using Wheel Reaction Torque

Abstract

In this paper, two nonlinear methods for stabilizing the orientation of a Four-Wheel Independent Drive and Steering (4WIDS) robot while in the air are analyzed, implemented in simulation, and compared. AGRO (the Agile Ground Robot) is a 4WIDS inspection robot that can be deployed into unsafe environments by being thrown, and can use the reaction torque from its four wheels to command its orientation while in the air. The goal of this work is to decrease the stabilization time and reject disturbances using nonlinear control methods. Model-based Feedback Linearization (FL) was added to PD control to compensate for nonlinear dynamics. However, with external disturbances, model uncertainty, and sensor noise the FL+PD controller does not guarantee stability. As an alternative, a backstepping controller was designed based on Lyapunov analysis with adaptive compensation for external disturbances, model uncertainty, and sensor offset. A simulation was written using the full nonlinear dynamics of AGRO in an isotropic steering configuration in which control authority over its pitch and roll are equalized. The PD+FL control method was compared to the backstepping control method using the same initial conditions in simulation. Both the backstepping controller and the PD+FL controller stabilized the system within 250 ms. The adaptive backstepping controller was also able to compensate for offset noisy sinusoidal disturbances through an adaptation law.