Particle swarm optimization of artificial-neural-network-based on-line trained speed controller for battery electric vehicle

13Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

Abstract

The paper presents implementation of PSO (Particle Swarm Optimization) to ANN-based speed controller tuning. Selected learning parameters are optimized according to the control objective function. A battery electric vehicle is considered as a potential plant for an adaptive speed controller. The need for adaptivity in the control algorithm is justified by variations of a total weight of the vehicle. A sizable section of the paper deals with selection of a combined objective function able to effectively evaluate the quality of a solution.

Cite

CITATION STYLE

APA

Ufnalski, B., & Grzesiak, L. M. (2012). Particle swarm optimization of artificial-neural-network-based on-line trained speed controller for battery electric vehicle. Bulletin of the Polish Academy of Sciences: Technical Sciences, 60(3), 661–667. https://doi.org/10.2478/v10175-012-0059-9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free