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.
Semantic control theory
Abstract An overview of a new methodology, involving the application of artifical intelligence techniques to the design and implementation of some decision and control systems, is given.
Artificial intelligence in air combat games
Abstract A general framework for the utilization of large numbers of optimal pursuit-evasion algorithms, as applied to air combat, is described. The framework is based upon and is driven by artificial intelligence concepts. The method employed involves the valuation of alternative tactical strategies and maneuvers through a goal system and pilot-derived expert data bases. The system is designed to display the most promising strategies to the pilot for a final decision. Two aspects of the concept above are described here: the general framework and a specific implementation for a synthetic method of flight and fire control system optimization. Details of the implementation, based on off-the-shelf hardware and a standard programming lanuage, are also given. Potential utilization of these concepts includes other areas as well: submarine warfare and satellite based weapon systems are two possible additional applications. Nonmilitary applications are air traffic control and optimal scheduling.