Abstract:
In this paper, two stabilizing nonlinear model
predictive control (NMPC) designs, namely, final-state equality
constraint stabilizing design and final-state inequality constraint
stabilizing design have been applied to achieve two wheeled
mobile robot’s control objectives, i.e. point stabilization and
trajectory tracking. In both controllers, final-state constraints
are imposed, on the online optimization step, to guarantee the
closed loop stability. As shown in the literature, both stabilizing
designs were addressed to be computationally intense; thus, their
real-time implementation is not tractable. Nonetheless, in this
work, a recently developed toolkit implementing fast NMPC
routines has been used to apply the two stabilizing designs on a
mobile robot research platform after developing a C++ code,
coupling the toolkit and the research platform’s software. Full
scale experiments implementing the two stabilizing designs are
conducted and contrasted in terms of performance measures and
real-time requirements.
