PSO-based nonlinear predictive control for unmanned bicycle robot stabilization

The paper considers vertical stabilization of an unmanned bicycle-like robot. Nonlinear predictive control is utilized for the purpose; at every step optimization of a nonlinear cost function using particle swarm optimization is performed. This allows to find optimal global solution or solution close to this optimum, depending on the employed time, even for nonconvex functions. Simulations show that this approach to model predictive control can provide satisfactory results.