Using Artificial Neural Networks (ANN) to Control Chaos
This addresses the problem of achieving stable energy output from chaotic resources for engineers and researchers in control systems, but it is incremental as it applies an existing ANN method to a known chaotic system.
The paper tackled controlling chaos in electronic systems, specifically using an artificial neural network (ANN) to stabilize a chaotic Chua circuit via simulation in NI's MultiSim, resulting in successful stabilization of hard-to-stabilize systems.
Controlling Chaos could be a big factor in getting great stable amounts of energy out of small amounts of not necessarily stable resources. By definition, Chaos is getting huge changes in the system's output due to unpredictable small changes in initial conditions, and that means we could take advantage of this fact and select the proper control system to manipulate system's initial conditions and inputs in general and get a desirable output out of otherwise a Chaotic system. That was accomplished by first building some known chaotic circuit (Chua circuit) and the NI's MultiSim was used to simulate the ANN control system. It was shown that this technique can also be used to stabilize some hard to stabilize electronic systems.