1 research outputs found
Comparing Feedback Linearization and Adaptive Backstepping Control for Airborne Orientation of Agile Ground Robots using Wheel Reaction Torque
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. Prior work has demonstrated
on a hardware prototype that simple PD control with hand-tuned gains is
sufficient, but hardly optimal, to stabilize the orientation in under 500ms.
The goal of this work is to decrease the stabilization time and reject
disturbances using nonlinear control methods. A model-based Feedback
Linearization (FL) was added to compensate for the nonlinear Coriolis terms.
However, with external disturbances, model uncertainty and sensor noise, the FL
controller does not guarantee stability. As an alternative, a second controller
was developed using backstepping methods with an adaptive compensator for
external disturbances, model uncertainty, and sensor offset. The controller was
designed using Lyapunov analysis. 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 milliseconds. The adaptive
backstepping controller was also able to achieve this performance with the
adaptation law enabled and compensating for offset noisy sinusoidal
disturbances.Comment: First Submission to IEEE Letters on Control Systems (L-CSS) with the
American Controls Conference (ACC) Optio