Distributed predefined-time neural adaptive attitude consensus of multiple spacecraft

This article presents a distributed predefined-time neural adaptive control scheme for the attitude consensus of multiple rigid spacecraft under inertia uncertainties and external perturbations through local communication. First, a predefined-time distributed observer is constructed for each follower spacecraft to estimate the virtual leader's attitude and velocity. Then, based on the recovered information, a predefined-time neural adaptive controller is exploited for each follower spacecraft to fulfil the local attitude tracking by utilising the neural network (NN) to identify the total unknown item. Particularly, the idea of indirect neural identification is introduced through inequality relaxation technique that each identification only requires a single learning parameter and thus the presented controller is computational efficient. Stability argument shows that the attitude and velocity synchronisation errors can stabilise to the minor regions around zero in predefined time. Lastly, comparative simulations validate and highlight the presented control scheme.