Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

Improved Genetic Algorithm Tuning Controller Design for Autonomous Hovercraft

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 t...

Full description

Bibliographic Details
Main Authors: Huu Khoa Tran, Hoang Hai Son, Phan Van Duc, Tran Thanh Trang, Hoang-Nam Nguyen
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Processes
Subjects:
modified ga
fuzzy-pid control
autonomous hovercraft
ise criterion
Online Access:https://www.mdpi.com/2227-9717/8/1/66
Description
Summary: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.
ISSN:2227-9717

Similar Items