LAUSR

This study presents a predictor-based adaptive feedback control for a class of systems with a known input time delay, an arbitrary large unknown output time delay, unmeasurable states, unmodelled dynamics and disturbances. First, a predictor is employed to cope with the input time delay, and an input delay-free system was established. Then, to overcome the arbitrarily large unknown output time delay and unmeasurable states, an augmented descriptor observer is developed for the new delay-free system. Finally, an adaptive neural network is constructed to estimate the lumped unknown term by backstepping control and obtain the preliminary estimated model, which can compensate the unknown dynamic disturbances and the unmodelled dynamics in the backstepping iteration to achieve the desired tracking performance. In addition, to demonstrate the efficiency of the proposed scheme, the control of pressure difference is also implemented in the adsorption system of an aircraft skin inspection robot, and the simulation results verify the feasibility and effectiveness of the proposed control scheme.