Research and Development of Selflearning Neural Network Algorithm for Optimal Energy-efficient Autonomous Electrical Unmanned Vehicles Motion Control
Doctoral Thesis
Aleksandrs Korņejevs, Riga Technical University, Latvia
Description
The Thesis is devoted to the research and development of a method for optimizing the energy consumption of electric unmanned vehicles for optimal energy-efficient control. The control structure of unmanned vehicles is described. A mathematical model of vehicle movement, a mathematical model of a neural network, and a self-learning algorithm for optimal energy consumption using a neural network are described. As a result, a new method was developed for optimizing the energy consumption of an electric unmanned vehicle, providing optimal energy efficiency with changing vehicle parameters, without preliminary calculations and settings.
About the author
Additional information
| Publication type | |
|---|---|
| Defence date | 29.12.2023. |
| Format | |
| Pages | 126 |
| Publication date | |
| Published online | |
| Publication language | |
| Publisher | RTU Press |
| Country of Publication | Latvia |
| Funding source |
