Neural Systems for Control

Control problems and neural networks

Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing application area of neural networks and focuses on research in natural and artificial neural systems directly applicable to control or making use of modern control theory.

Key developments covered

The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft, aircraft, and other systems; applications to rolling mills, robotics, and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control.

Intended audience

All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance.

Highlights

- Focuses on research in natural and artificial neural systems directly applicable to control or making use of modern control theory
- Represents the most up-to-date developments in this rapidly growing application area of neural networks
- Takes a new and novel approach to system identification and synthesis