Continuous-time and sampled data stabilizers for nonlinear systems with input and measurement delays

In this paper, we propose continuous-time and sampled-data output feedback controllers for nonlinear multi-input multi-output systems with time-varying measurement and input delays, with no restriction on the bound or serious limitations on the growth of the nonlinearities. A state prediction is generated by chains of saturated high-gain observers with switching error-correction terms and the state prediction is used to stabilize the system with saturated controls. The observers reconstruct the unmeasurable states at different delayed time-instants, which partition the maximal variation interval of the time-varying delays. These delayed time instant depend both on the magnitude of the delays and the growth rate of the nonlinearities. We also design sampled-data stabilizers as zero-order discretization of a hybrid modification (with continuous-time states and discrete-time control and innovations) of the continuous-time stabilizers.