Tracking control algorithms for plants with input time-delays based on state and disturbance predictors and sub-predictors

摘要

The novel control algorithm for linear time invariant plants with input time-delays and presence of external disturbances is proposed. The algorithm based on the state and disturbance predictors ensures the tracking control with unknown reference model parameters. The accuracy in steady state depends on the highest derivative of disturbance and reference model signals, therefore, the magnitude of these signals can be sufficiently large. Further, the proposed algorithm are extended on the state and disturbance sub-predictors which implement multi-step prediction. Compared with the predictor based algorithm the sub-predictor based algorithm allows to control plants with a larger input time-delay and allows to predict the disturbance in less time. The sufficient conditions in terms of linear matrix inequalities (LMIs) provide the estimate of the maximum time-delay that preserves the closed-loop system stability. Numerical examples illustrate the efficiency of the designed method compared with some existing ones. (C) 2019 Published by Elsevier Ltd on behalf of The Franklin Institute.