Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Mario G. Perhinschi"'
Autor:
Aaron R. Mull, Andrew C. Nix, Mario G. Perhinschi, W. Scott Wayne, Jared A. Diethorn, Dawson E. Dunnuck
Publikováno v:
Journal of Transportation Technologies. 12:804-832
Autor:
Aaron R. Mull, Mario G. Perhinschi, W. Scott Wayne, Andrew C. Nix, Jared A. Diethorn, Thomas P. Harris
Publikováno v:
Journal of Transportation Technologies. 11:471-503
Continued increases in the emission of greenhouse gases by passenger vehicles have accelerated the production of hybrid electric vehicles. With this increase in production, there has been a parallel demand for continuously improving strategies of hyb
Investigation of Alternative Parameters for Immunity-based UAV Navigation in GNSS-denied Environment
Autor:
Mario G. Perhinschi, Mohanad Alnuaimi
Publikováno v:
Unmanned Systems. :65-72
This paper is focused on analyzing effects of several significant parameters on the performance of an immunity-inspired methodology for autonomous navigation of unmanned air vehicles when measurements from global navigation satellite systems (GNSS) o
Publikováno v:
International Journal of Intelligent Unmanned Systems. 9:237-255
PurposeAn artificial immune system (AIS) for the detection and identification of abnormal operational conditions affecting an unmanned air vehicle (UAV) is developed using the partition of the universe approach. The performance of the proposed method
Autor:
Ryan McLaughlin, Mario G. Perhinschi
Publikováno v:
AIAA SCITECH 2022 Forum.
Autor:
Ryan McLaughlin, Mario G. Perhinschi
Publikováno v:
AIAA SCITECH 2022 Forum.
Publikováno v:
AIAA SCITECH 2022 Forum.
Publikováno v:
International Journal of Intelligent Unmanned Systems. 7:19-34
Purpose The purpose of this paper is to develop and implement a general sensor model under normal and abnormal operational conditions including nine functional categories (FCs) to provide additional tools for the design, testing and evaluation of unm
Autor:
Mridul Gautam, Marc Besch, Pragalath Thiruvengadam, Mario G. Perhinschi, Ross Ryskamp, Arvind Thiruvengadam, Berk Demirgok, Daniel K. Carder
Publikováno v:
SAE International Journal of Engines. 13
Publikováno v:
Computers & Chemical Engineering. 117:378-390
In this article, a novel approach is proposed for integrating a Biologically-Inspired Optimal Control Strategy (BIO CS) with an Artificial Neural Network (ANN)-based adaptive component for advanced energy systems applications. Specifically, BIO CS em