Online model predictive control tuning using kalman algorithm applied to a vertical take-off and landing platform

Model Predictive Control (MPC) is an optimal algorithm which is having impressive performances on industrial field. However, to implement an MPC on practical fast dynamics systems is essential to avoid the computational load of the algorithm. In many cases, controller tuning is made using heuristic methods that cannot be generalized for other processes. In the present work, the implementation of MPC with online tuning through an Extended Kalman Filter (EKF) is applied to a Vertical Take - Off and Landing Platform (VTOL). The position tracking results of the VTOL are evaluated under different initial conditions of the EKF. The best control performance is determined by evaluating the Integral of Absolute Error value (IAE) criterion.