Non-Linear Model-Based Predictive Control For Trajectory Tracking And Control Effort Minimization In A Smartphone-Based Quadrotor

In this paper, the design and implementation of a nonlinear model-based predictive controller (NMPC) for predefined trajectory tracking and to minimize the control effort of a smartphone-based quadrotor are developed. The optimal control actions are calculated in each iteration by means of an optimal control algorithm based on the non-linear model of the quadrotor, considering some aerodynamic effects. Control algorithm implementation and simulation tests are executed on a smartphone using the CasADi framework. In addition, a technique for estimating the energy consumed based on control signals is presented. NMPC controller performance was compared with other works developed towards the control of quadrotors, based on an H_∞ controller and an LQI controller, and using three predefined trajectories, where the NMPC average tracking error was around 50% lower, and average estimated power and energy consumption slightly higher, with respect to the H_∞ and LQI controllers.