Nonlinear model predictive control with constraint satisfactions for a quadcopter
European Workshop on Advanced Control and Diagnosis (ACD)
This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the eectiveness of the proposed strategy.
Y. Wang, A.F. Ramírez, F. Xu and V. Puig. Nonlinear model predictive control with constraint satisfactions for a quadcopter, 13th European Workshop on Advanced Control and Diagnosis, 2016, Lille, Vol 783 of Journal of Physics: Conference Series, pp. 1-12, 2017.