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Adaptive Model Predictive Control of Wheeled Mobile Robots

arXiv 2201.00863 ↗First posted 3 Jan 2022cs.RO cs.AI cs.SYcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 18 references that are in the map. First posted on arXiv 3 Jan 2022.

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References · 1

  1. 2018Adaptive Model Predictive Control for High-Accuracy Trajectory Tracking in Changing Conditionscited by 7

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