Reduced-order Multiple Models Robust Direct Adaptive Control of Non-minimum Phase System

摘要

The performance of robust adaptive control system based on traditional revised algorithm is awful in the presence of unmodeled dynamics and the performance will go bad, even be unstable, when the working condition (including the parameter, reference input, and so on) change. This paper designs the multiple models robust adaptive controller to control the discrete single-variable non-minimum phase system. First, the higher part of the system is deem to be the unmodelled dynamic and the normalization is introduced to convert the system unmodeled dynamics to bounded disturbance as well as the dead zone is introduced in parameter update algorithm. And then, the multiple models robust adaptive controllers are designed based on the lower part of the system and the best controller is chosen based on the switch index to control the system. The last simulation illustrates that the proposed method is preferable even the working condition changes.