The application of neural computing to the design of highly reliable, space-power systems is addressed by using neural network techniques to implement a set of conventional control algorithms. This set will include the classical PID (proportional integral derivative) control algorithm, latching and non-latching alarm blocks, and current-time functions. Conceptually the neural-based control system building blocks will perform like their traditional counterparts which are well-understood and commonly used by system designers. The underlying implementation, however, will be founded on highly distributed neural networks designed to run as software in a network of microprocessors with the potential for adaptation to dedicated neural processors. The ultimate goal is the integration of highly developed and well-understood power control techniques with neural systems, whose inherent fault tolerance, speed, and light weight are advantageous in space applications.
Potential Commercial Applications:Applications could include power distribution networks, power plants, chemical processing, environmental systems, security systems, traffic control, aircraft power units, medical life support, and automated manufacturing.STATUS: Phase I Only
