Intelligent control for autonomous systems

Author

Passino, Kevin M.

Author_Institution

Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA

Volume

32

Issue

6

fYear

1995

fDate

6/1/1995 12:00:00 AM

Firstpage

55

Lastpage

62

Abstract

Intelligent control is the discipline in which control algorithms are developed by emulating certain characteristics of intelligent biological systems. It is quickly emerging as a technology that may open avenues for significant advances in many areas. In fact, fueled by advancements in computing technology, it has already achieved some very exciting and promising results. Here, the author argues that a mixture of intelligent and conventional control methods may be the best way to implement autonomous control systems

Keywords

digital control; fuzzy control; genetic algorithms; intelligent control; learning systems; mobile robots; neurocontrollers; optimal control; autonomous systems; computing technology; control algorithms; control system design; conventional control methods; fuzzy learning control; fuzzy supervisory control; intelligent biological systems; intelligent control; knowledge-based control; neural networks; Biological control systems; Control systems; Fuzzy systems; Humans; Intelligent control; Nonlinear control systems; Optimal control; Process control; Remotely operated vehicles; Robot kinematics;

fLanguage

English

Journal_Title

Spectrum, IEEE

Publisher

ieee

ISSN

0018-9235

Type

jour

DOI

10.1109/6.387144

Filename

387144