Barrier Lyapunov function-based adaptive output feedback failure compensation for a class of non-linear systems with unknown dead-zone non-linearity

In this paper, an adaptive robust output feedback control approach is proposed for a class of uncertain non-linear systems with unknown input dead-zone non-linearity, unknown failures and unknown bounded disturbances. By constructing the dead-zone inverse and applying the backstepping recursive design technique, a robust adaptive backstepping controller is proposed, in which adaptive control law is synthesized to handle parametric uncertainties and a novel robust control law to attenuate disturbances. The robust output feedback control law is developed by integrating a switching function σ algorithm at each step of the backstepping design procedure. In addition, K-filters are designed to estimate the unmeasured states and neural networks are employed to approximate the unknown non-linear functions. By ensuring boundedness of the barrier Lyapunov function, the major feature of the proposed controller is that it can theoretically guarantee asymptotic output tracking performance, in spite of the presence of unknown input dead-zone non-linearity, various actuator failures and unknown bounded disturbances via Lyapunov stability analysis. The effectiveness of the proposed approach is illustrated by the simulation examples.