Adaptive Robust Control of an Avian-Inspired Robot in Grasping Oscillatory Objects

The aim of this research work is to design an innovative adaptive robust nonlinear controller for an avian-inspired robot in grasping oscillatory objects based on an accurate extended model in planar motion. The unknown dynamics of the oscillatory objects together with the usual simplification made on the model to have an appropriate structure for controller design, can force intense disturbances and uncertainties that may lead the control system to be failed. In order to meet the goals of precise tracking along with desired transient response, this study proposes a control system based on adaptive generalized super-twisting sliding mode algorithm (A-GSTSMA) for this MIMO under-actuated aerial robot which is able to estimate the upper bounds of lumped disturbances/uncertainties and target's mass simultaneously through applying an adaptive gain tuning law together with an estimator. In this respect, compared with two other developed robust algorithms, the detailed performance and robust analyses are carried out via comprehensive numerical and Monte Carlo simulations in the wide range of flight speeds, measurement noise and uncertainties. The results demonstrate high efficiency of the proposed control scheme in enabling the flying system to track hybrid trajectories accurately.