A Predictor-Based Linearization Approach for Local Stabilization of Nonlinear Systems With Input Delay

In this article, a predictor-based linearization approach is presented to solve the local asymptotic stabilization (LAS) problem of time-invariant nonlinear systems with a large constant input delay. Under stabilizability and detectability of the linearized time-delay system, we prove that LAS is achievable by either predictor-based state or output feedback controllers, which are designed based on the linearization. The predictor-based linearization technique developed in this research complements the previous work and improves its result by removing the forward completeness condition and a number of technical requirements as well as by expanding the class of nonlinear systems with input delay to the general case. Examples are given to demonstrate the application of the predictor-based linearization technique.