Prediction-based Adaptive Robust Tracking Control of an Uncertain First-Order Time-Delay System

Abstract

This paper considers the tracking problem of a delayed uncertain first-order system which is simultaneously subject to (possibly large) known input delay, unknown but bounded time-varying disturbance, and unknown plant parameter. The proposed predictor adaptive robust controller (PARC) involves prediction-based projection type adaptation laws with model compensation and prediction-based continuous robust feedback such that the closed loop system has global exponential convergence with an ultimate bound proportional to delay, disturbance bound, and switching gain. Further, if there are only delay and parameter uncertainties after some finite time, then semi-global asymptotic tracking is guaranteed. The proposed design is shown to have significant closed loop performance improvement over the baseline controller.