Model-based predictive control for trajectory tracking of a quadrotor

Resumen: This paper presents the design of a model-based predictive controller (MPC) for trajectory tracking of a quadrotor. The dynamic model is obtained using the EulerLagrange equations of motion; the resulting model is linearized around the hovering condition. The optimal control sequence is applied by following the receding horizon principle. The optimization problem is based on a quadratic cost function, which incorporates the state errors and the vector of control inputs. This process is repeated at each sampling instant, considering the plant model as well as possible constraints. Numerical simulations validate the controller’s performance, which makes the vehicle follow the desired trajectory precisely.

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Eduardo Salazar Hidalgo, Josefina Castañeda Camacho, César Martínez Torres & Jose Martinez-Carranza . Model-based predictive control for trajectory tracking of a quadrotor. Memorias del Congreso Nacional de Control Automático, pp. 1-6, 2020.

Palabras clave

Euler-Lagrange, linearization, predictive control, MPC, trajectory tracking

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