  In this work, the control of snake robot locomotion via economic model
predictive control (MPC) is studied. Only very few examples of applications of
MPC to snake robots exist and rigorous proofs for recursive feasibility and
convergence are missing. We propose an economic MPC algorithm that maximizes
the robot's forward velocity and integrates the choice of the gait pattern into
the closed loop. We show recursive feasibility of the MPC optimization problem,
where some of the developed techniques are also applicable for the analysis of
a more general class of system. Besides, we provide performance results and
illustrate the achieved performance by numerical simulations. We thereby show
that the economic MPC algorithm outperforms a standard lateral undulation
controller and achieves constraint satisfaction. Surprisingly, a gait pattern
different to lateral undulation results from the optimization.
