Neural Networks

Sarah Ezzell

Engr. 315

What Are They?

Information processing system (non-algorithmic, non-digital)

Inspired by the human brain Made of artificial neurons (neurodes)

– Crude approximation of biological neurons– Connected by weights over which signals travel– Arranged in layers

Neural Network Diagram

Input Layer

Middle Layer

Output Layer

Input Signals

Output Signals

Neurode

Connection Link

Translation – Input Stimuli to Output Response

3 steps– Neurode computes net weighted input received– Converts net input into an activation level– Converts activation level into output signal

Learning Capability

Learns to solve problems, not just programmed Learning achieved by modifying weights Training methods

– Supervised– Graded– Unsupervised

Control System Applications

Aircraft Manufacturing plant Power plant

Aircraft – Flight Control System

Neural network like a human, but better– Adapts like human, only quicker and more

accurately

Back propagation vs. on line learning Network integrated with current flight control

systems– Removes “gain scheduling”

Manufacturing Plant – Hot Dip Galvanized Steel Strip

Manually controlled coating thickness controls Neural network control model

– Developed by Siemens and Thyssen Stahl– Cost-effective, better quality product– On line learning

Eliminates need for hot measuring equipment

Power Plant – Utility Boilers

Air pollutants from power plants NeuSIGHT system

– Used in coal-fired electric power plants– Provides real time closed-loop supervisory control– Improves operating efficiency & reduces emissions