An efficient model predictive control for trajectory tracking of wheeled inverted pendulum vehicles with various physical constraints

This study presents a robust model predictive control (MPC) strategy to handle the trajectory tracking problem for a underactuated two-wheeled inverted pendulum (WIP) vehicle, in addition to taking various physical constraints into account. To begin with, a saturated trajectory generator is proposed to produce the desired velocities by which all posture tracking errors converge to the compact sets as well as the saturation of velocities being guaranteed. In addition, a MPC approach is put up forward after the approximate feedback linearization is performed to decrease the burden of computation and increase the realtime performance of the control system. Particularly, various physical constraints can be readily assured by the presented MPC method although the equilibrium of WIP vehicle is unstable. Meanwhile, to validate the robustness and availability of the proposed approach, initial errors, pulse disturbance and random noise are introduced to test the control performance of the closed-loop system in the simulation environment. The results from both theoretical analysis and simulation show that the proposed control strategy are effective and feasible for practical implementation.