Reduced-order filter based output-feedback adaptive control for perturbed nonlinear systems

In this paper, a robust adaptive output-feedback control approach is presented for a class of nonlinear output-feedback systems with parameter uncertainties and time-varying bounded disturbances. A reduced-order filter driven by control input is proposed to reconstruct unmeasured states. The state estimation error is shown to be bounded by dynamic signals driven by system output. Based on the backstepping design with three set of tuning functions, adaptive output-feedback control scheme with the flat-zone modification is proposed. It is shown that all the signals in the resulting closed-loop adaptive control systems are bounded, and the output tracking error converges to a pre-specified small neighborhood of the origin. A simulation example is provided to illustrate the effectiveness and validity of the proposed approach.