Adaptive Model Predictive Control of Wheeled Mobile Robots
Prakash, Nikhil Potu Surya, Perreault, Tamara, Voth, Trevor, Zhong, Zejun
–arXiv.org Artificial Intelligence
In this paper, a control algorithm for guiding a two wheeled mobile robot with unknown inertia to a desired point and orientation using an Adaptive Model Predictive Control (AMPC) framework is presented. The two wheeled mobile robot is modeled as a knife edge or a skate with nonholonomic kinematic constraints and the dynamical equations are derived using the Lagrangian approach. The inputs at every time instant are obtained from Model Predictive Control (MPC) with a set of nominal parameters which are updated using a recursive least squares algorithm. The efficacy of the algorithm is demonstrated through numerical simulations at the end of the paper.
arXiv.org Artificial Intelligence
Jan-3-2022
- Country:
- North America > United States
- California (0.14)
- Massachusetts (0.14)
- New York (0.14)
- North America > United States
- Genre:
- Research Report (0.40)
- Technology:
- Information Technology > Artificial Intelligence > Robots > Locomotion (0.93)