Decentralized Predictor Feedback of Large-scale Systems under Input Delays

Abstract

This paper develops a decentralized predictor feedback approach for large-scale interconnected systems with large input delays. The local control law proposed in this paper does not employ information from other neighbors. We propose two methods for the delay compensation: the backstepping-based predictor and the one based on the reduction approach. The first one leads to simpler conditions and manages with larger delays, whereas the second can be easily applied to sampled-data implementation with asynchronous sampling instants. Through a benchmark example of two coupled cart-pendulum systems, the proposed approach is demonstrated to be effective when the input delays are too large for the system to be stabilized without a predictor.