Neurocontrol: Learning Control Systems Inspired by Neuronal Architectures and Human Problem Solving Strategies (Lecture Notes in Control and Information Sciences, 172)

Tolle, H.

ISBN 10: 3540550577 / ISBN 13: 9783540550570

Editore: Springer, 1992

Riguardo questo articolo

Codice articolo ABLIING23Mar3113020170267

Dati bibliografici

Titolo: Neurocontrol: Learning Control Systems ...

Casa editrice: Springer

Data di pubblicazione: 1992

Legatura: Brossura

Condizione: New

Descrizione articolo

Riassunto:

Since heavily non-linear and/or very complex processes stillpose a problem for automatic control, they can often behandled easily by human operators. The book describes re-sults from ten years of research on learning control loops,which imitate these abilities. After discussing the diffe-rencesto adaptive control some background on human informa-tion processing and behaviour is put forward and some lear-ning control loop structure related to these ideas is shown.The ability to learn is due to memories, which are able tointerpolate for multi-dimensional input spaces between scat-tered output values. A neuronally and mathematically inspi-red memory lay out-are compared and it is shown that theylearn much faster thanbackpropagation neural networks,which can also be used. For the learning control loop diffe-rent architectures are given. Their usefulness is demonstra-ted by simulation and results from applications to real pi-lot plants. The book should be of interest for control engi-neers as well as researchers in neural net applicationsand/or artificial intelligence. The usual mathematical back-ground of engineers is sufficient.

Contenuti:

Basic considerations.- Microintelligence.- Macrointelligence.