Version 1
: Received: 8 October 2024 / Approved: 8 October 2024 / Online: 17 October 2024 (10:17:39 CEST)
How to cite:
Aro, K.; Guevara, L.; Prado, A. Robust Nonlinear Model Predictive Control for Trajectory Tracking of Skid Steer Mobile Manipulators with Wheel-Ground Interactions. Preprints2024, 2024101352. https://doi.org/10.20944/preprints202410.1352.v1
Aro, K.; Guevara, L.; Prado, A. Robust Nonlinear Model Predictive Control for Trajectory Tracking of Skid Steer Mobile Manipulators with Wheel-Ground Interactions. Preprints 2024, 2024101352. https://doi.org/10.20944/preprints202410.1352.v1
Aro, K.; Guevara, L.; Prado, A. Robust Nonlinear Model Predictive Control for Trajectory Tracking of Skid Steer Mobile Manipulators with Wheel-Ground Interactions. Preprints2024, 2024101352. https://doi.org/10.20944/preprints202410.1352.v1
APA Style
Aro, K., Guevara, L., & Prado, A. (2024). Robust Nonlinear Model Predictive Control for Trajectory Tracking of Skid Steer Mobile Manipulators with Wheel-Ground Interactions. Preprints. https://doi.org/10.20944/preprints202410.1352.v1
Chicago/Turabian Style
Aro, K., Leonardo Guevara and Alvaro Prado. 2024 "Robust Nonlinear Model Predictive Control for Trajectory Tracking of Skid Steer Mobile Manipulators with Wheel-Ground Interactions" Preprints. https://doi.org/10.20944/preprints202410.1352.v1
Abstract
This paper presents a robust control strategy for trajectory tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimizes trajectory tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy aims to counteract disturbance effects caused by the slip phenomena through the wheel-terrain contact and bidirectional interactions propagated by the mechanical coupling between the SSMM base and arm. To capture such interactions, the mobile base dynamics and arm joints consider a coupled nonlinear model with bounded uncertainties based on principles of full-body energy balance and link torques. In addition, the SSMM dynamics stands by dynamical models, which are capable of capturing nonlinear speed relationships. Thus, a centralized control architecture integrates a nominal and ancillary controller based on the Active Disturbance Rejection Control (ADRC) to strengthen robustness of the Nonlinear Model Predictive Control (NMPC), operating the SSMM dynamics as a single robotic body. The NMPC is responsible for trajectory tracking control of a five Degrees of Freedom (DoF)’s SSMM. Meanwhile, the ADRC uses an Extended State Observer (ESO) to quantify the impact of external disturbances and uncertainties, generating compensation for unmeasurable disturbances. In addition, the proposed robust control strategy compensates for the model mismatch errors, which are generated by the difference between an SSMM nominal model (disturbance-free) and its real-time response. Results indicate that the approach is able to compensate for effects by 70% using pre-set trajectories and regulation tests against unmeasurable disturbances applied to simulated SSMR model.
Keywords
Robust Nonlinear Model Predictive Control; Active Disturbance Rejection Control; Skid-Steer Mobile Manipulator; Wheel Terrain Interaction
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
