Data driven adaptive robust attitude control for a small size unmanned helicopter

In this paper, the data driven based control design problem for a small size unmanned helicopter is investigated. The helicopter is subjected to the effects associated with modeling uncertainties and unknown external disturbances. A new model free robust adaptive attitude control law is proposed with the combination of the model-free-adaptive-control (MFAC) design, the immersion and invariance (I&I) approach, and the super-twisting technique. Different from the most existing linear or nonlinear model-dependent control designs for unmanned helicopters, the proposed control strategy requires very less model knowledge. The controller depends mainly on the input and output data of the helicopter, and no boundedness knowledge of the unknown disturbances is required. Stability of the closed-loop system has been proved. Real-time flight experiments have been performed on the self-developed helicopter testbed only with the available feedback data of the helicopter. The experimental results have validated the good robustness of the proposed control methodology.