Uncertainty equivalence principle and H∞-based robust adaptive control: Stable plants
A novel idea, termed as uncertainty equivalence principle, is proposed, based on which an equivalent measure to the H∞-norm is adopted for unmodeled dynamics using time-domain measurement data. Such an equivalent description for modeling errors is consistent with H∞-based robust control, and allows H∞ optimization to be successfully used in adaptive control to achieve robust stability and performance comparable to H∞ control. Specifically a new adaptive control systems is proposed in this paper, focusing on stable plants. It employs the recursive least-squares (RLS) algorithm for adaptive model estimation, and weighted sensitivity minimization plus robust stabilization for adaptive controller design. Our results show that the proposed adaptive control system admits robust stability and performance asymptotically, provided that the estimated plant model converges.
Publication Source (Journal or Book title)
Proceedings of the IEEE Conference on Decision and Control
Gu, G., & Qiu, L. (2002). Uncertainty equivalence principle and H∞-based robust adaptive control: Stable plants. Proceedings of the IEEE Conference on Decision and Control, 3, 3055-3060. Retrieved from https://repository.lsu.edu/eecs_pubs/321