Adaptive Model Predictive Control of Wheeled Mobile Robots
This work addresses a domain-specific control problem for wheeled mobile robots, presenting an incremental improvement by combining MPC with adaptive parameter updates.
The paper tackles the problem of controlling a two-wheeled mobile robot with unknown inertia to a desired position and orientation using an Adaptive Model Predictive Control (AMPC) framework, and demonstrates its efficacy through numerical simulations.
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.