RBF-Learning-Based Many-Objective Metaheuristic for Robust and Optimal Controller Design in Fixed-Structure Heading Autopilot

RBF-Learning-Based Many-Objective Metaheuristic for Robust and Optimal Controller Design in Fixed-Structure Heading Autopilot

This paper presents an innovative many-objective metaheuristic (MnMH) algorithm designed to tackle the challenges of robust and optimal controller design for fixed-structure heading autopilots. The proposed approach leverages the radial basis function (RBF)-learning operator during the reproduction...

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Bibliographic Details
Main Authors: Nattapong Ruenruedeepan, Sujin Bureerat, Natee Panagant, Nantiwat Pholdee
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Aerospace
Subjects:
fixed-structure robust controller design
metaheuristics
autopilot design
many-objective optimization
surrogate model
Online Access:https://www.mdpi.com/2226-4310/12/6/461
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