Indirect Adaptive Predictor Preview Control with Unknown Time Varying Input Delay and Parameter

Abstract

This paper presents an indirect adaptive predictor–preview control architecture for continuous-time systems with unknown time-varying input delays and unknown (slowly varying) parameters. An adaptive super-twisting algorithm (STA) estimates the unknown delay online using a monotone ramp probe, and an indirect recursive least-squares (RLS) module tracks slow parameter variations; both feed a frozen-parameter predictor and a preview feedforward-based on r(t + ˆ h(t)). Nominal exponential tracking is shown under exact prediction, and a practical input-to-state The stability (ISS) bound is derived that accounts for delay/parameter estimation errors, disturbances, and numerical approximation. On the DC motor speed servo benchmark, the controller reduces steady state RMSE/peak error to 0.046/0.074 (S1) and 0.062/0.099 (S4), below all compared baselines.