Pattern recognition-based supervision of indirect adaptation for better disturbance handling.

An advanced pattern recognition-based supervision algorithm for an indirect adaptive controller is proposed. The aim is to improve performance under certain conditions that are common in the industrial environment, in which indirect adaptive controllers with simple supervision are known to perform poorly or unreliably. Specifically, the problem of large invasive unmeasured disturbances of short or longer duration is addressed.