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 con‐ trol 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.