基于ANFIS的飞行器自动着陆模糊控制器设计

Design of an Aircraft Auto-landing Fuzzy Controller Based on ANFIS

首先给出了模糊逻辑控制器设计中的几点共同的基本假设,接着阐述了飞行器降落着陆过程自动控制的模糊控制器AFLC的控制原理,详细分析和设计了AFLC的自动着陆控制模型、状态变量的隶属函数、系统推理规则、模糊推理算法和解模糊算法等。重点对基于自适应神经模糊推理ANFIS的Takagi-Sugeno型AFLC进行了优化分析与设计。最后利用MATLAB的Simulink仿真工具和模糊逻辑工具箱对两种设计方案进行了仿真验证和分析比较。仿真结果表明,两种AFLC设计是有效的,后者性能更优。

The common basic hypotheses in the design of a fuzzy logic controller are first proposed. The active principles of an Aircraft auto-Landing Fuzzy Controller in the course of automatic control on landing are investigated. The auto-landing model in control, membership functions of state variables, inference rules in the system, algorithms for fuzzy inference and defuzzication, etc., are analyzed and devised in detail with an emphasis on optimal analysis and design of Takagi-Sugeno ALFC based on Adaptive Neural Fuzzy Inference Systems. Finally, the verification via simulation and comparisons in analysis for the two designed schemes are made by using Simulink and Fuzzy Logic Toolbox with MATLAB. The simulated results show that both the ALFC schemes are available and the latter is superior in performance.