Multi-Objective Design Optimization of an Intelligent Altitude Controller for a Nonlinear Aircraft Using Fuzzy Logic and Genetic Algorithms

Setayandeh, Mohamamdreza

doi:10.22034/jast.2025.541185.1232

Multi-Objective Design Optimization of an Intelligent Altitude Controller for a Nonlinear Aircraft Using Fuzzy Logic and Genetic Algorithms

Articles in Press

Document Type : Original Article

Author

Mohamamdreza Setayandeh

Department of Mechanical Engineering, Shahreza Campus, University of Isfahan, Isfahan, Iran

10.22034/jast.2025.541185.1232

Abstract

The objective of this paper is to design an altitude controller for an aircraft using fuzzy logic and genetic algorithms. In this study, two methods (specialist experience and scale mapping) are used to develop the fuzzy rules. First, a basic fuzzy controller is designed using both methods. Then the centers of the membership functions of inputs and outputs are determined using genetic algorithm, aiming to reduce control effort, steady-state error, and rise time. The TOPSIS method is employed to select the final solution. The results show that, on average, the optimized fuzzy controllers achieve performance improvements of 28%, 53%, and 15% in control effort, steady-state error, and rise time, respectively. Finally, robustness analysis is conducted for the optimized fuzzy controllers in the presence of uncertainties: sensor noise, different aerodynamics derivatives, changing flight conditions, and gust. The results indicate that the optimized fuzzy controller based on specialist experience demonstrates robust performance.

Keywords

Altitude controller

Fuzzy logic

Genetic algorithm

Nonlinear dynamics

Multi-objective optimization

Subjects