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

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 ۲۸%, ۵۳%, and ۱۵% 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.

کلیدواژه ها:

Altitude controller ، Fuzzy logic ، Genetic Algorithm ، nonlinear dynamics ، Multi-Objective Optimization