Adaptive model predictive control-based attitude and trajectory tracking of a VTOL aircraft

A novel adaptive model-based predictive controller for attitude and trajectory tracking of a vertical take-off and landing (VTOL) aircraft in the simultaneous presence of model uncertainties and external disturbances is introduced in this study. An important challenge of designing the model-based controllers is developing an accurate model, especially in the presence of model uncertainties. In this study, first, the nominal model of a ducted-fan air vehicle, which is a multi-input multi-output nonlinear system with non-minimum phase behaviour, is given as the test case of this research. After that, two modified robust and adaptive model predictive controllers are proposed for tracking a predefined path in the presence of external gusts and model uncertainties. The design is performed by introducing two novel observers to estimate the model uncertainties and external disturbances, simultaneously. Different types of input constraints, as well as the time delay of the system inputs, can be considered effectively in the design steps of the proposed control strategy. The stability of the closed-loop system is proved under a few realistic assumptions. The simulation results demonstrate the great capability of the proposed method for attitude and trajectory tracking of the VTOL aircraft under model uncertainties and wind turbulence.