Time optimal control of mobile robot motion using neural nets

M. Kemal Ciliz, Can Isik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

A multilayer neural network architecture is proposed as a trainable controller for realizing time-optimal switching surfaces. The locomotion mechanism of a mobile robot is modeled by a double integrator dynamic system with linear acceleration as the control input to the actuators. A four-layer feedforward neural network is then trained, using a collection of representative samples chosen from a certain region of the state space, to realize a continuous mapping between the system's states and optimal control actions. This network is then used as part of a specified control loop. Simulation of the overall system generated nearly optimal state trajectories.

Original languageEnglish (US)
Title of host publicationProc IEEE Int Symp Intell Control 1989
EditorsArthur C. Sanderson, Alan A. Desrochers, Kimon Valavanis
PublisherIEEE Computer Society
Pages368-373
Number of pages6
ISBN (Print)0818689870
StatePublished - Dec 1 1989
EventProceedings: IEEE International Symposium on Intelligent Control 1989 - Albany, NY, USA
Duration: Sep 25 1989Sep 26 1989

Publication series

NameProc IEEE Int Symp Intell Control 1989

Other

OtherProceedings: IEEE International Symposium on Intelligent Control 1989
CityAlbany, NY, USA
Period9/25/899/26/89

ASJC Scopus subject areas

  • Engineering(all)

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