Applications of A.I. in control systems

This Paper Presents a case study of an aircraft central system that can tolerate control surface failures using Semantic control theory. In this application, the semantic control system uses system identification and the control mixer concept to exploit the analytical or control redundancy among the control surfaces and thus accommodate the failures. System identification Is performed using artificial intelligence techniques. With this approach unpredictable faults can also be accomodated, which is normally not realized using the conventional techniques.