Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

PhD.Phan Van DucHuu Khoa Tran, Hoang Hai Son, Tran Thanh Trang, Hoang-Nam Nguyen

Faculty of Automotive Engineering

Research output: Article

researchs.abstract

By mimicking the biological evolution process, genetic algorithm (GA) methodology has the advantages of creating and updating new elite parameters for optimization processes, especially in controller design technique. In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed to find the optimized fuzzy-proportional-integral-derivative (fuzzy-PID) control parameters. Due to minimizing tracking error of the controller design criterion, the fitness function integral of square error (ISE) was employed to utilize the advantages of the modified GA. The proposed method was then applied to a novel autonomous hovercraft motion model to display the superiority to the standard GA.

Overview
Type
Article
Publication year
03 Jan 2020
Original language
English
Published Journal
Processes, Processes
Volume No
8 (1)
Classification
ISI Indexed
ISSN index
2227-9717
Quartiles
Q2

Access Document Overview

To read the full-text of this publication, you can request a copy directly from the authors.