Intelligent flight controllers for helicopter control
Intelligent flight controllers for helicopter control
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DOI：
10.1109/icnn.1997.616092
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发表时间：
1997-06
期刊：
影响因子：
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通讯作者：
S. Zein-Sabatto;Yixiong Zheng
中科院分区：
文献类型：
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作者：
S. Zein-Sabatto;Yixiong Zheng
本文提出了一种智能直升机飞行控制器的设计方法。该方法结合了人工神经网络，遗传算法，传统的PID控制器，模糊逻辑算法的设计过程中。在这种方法中，智能控制器的设计是基于从实际直升机飞行中收集的实验数据，而不是基于分析模型。训练神经网络学习直升机的动态特性。基于神经网络模型，采用遗传算法搜索用于叶片角度控制的PID控制器的系数。通过对直升机气动力学理论的理解和对直升机试验飞行数据的分析，利用模糊逻辑算法设计了主旋翼转速控制器。将桨叶角PID控制器和旋翼转速模糊控制器相结合，构成智能直升机飞行控制器。仿真结果表明，对于所需的高度输入H/sub d/，智能控制器能够产生适当的控制信号，用于叶片角度控制和转子速度控制。直升机模型高度输出H/sub t/跟随期望高度输入H/sub d/。本文介绍了设计过程、理论背景、结果和结论。
A methodology for design of an intelligent helicopter flight controller is presented in this paper. The methodology combines artificial neural network, genetic algorithms, conventional PID-controllers, and fuzzy logic algorithms in the design procedure. In this approach, the design of an intelligent controller is based on experimental data collected from actual helicopter flight and not based on analytical models. A neural network is trained to learn the dynamic characteristics of the helicopter. Based on the neural model, the coefficients of a PID-controller used for blade angle control are searched for using genetic algorithms. The main rotor speed controller is designed using fuzzy logic algorithm based on knowledge generated from understanding the aerodynamic theory and analyzing the helicopter experimental flight data. The intelligent helicopter flight controller is formed by combining the blade angle PID-controller and the rotor speed fuzzy controller. Simulation results showed that for desired altitude input H/sub d/, the intelligent controller was able to generate proper control signals for both the blade angle control and the rotor speed control. The helicopter model altitude output H/sub t/ follows the desired altitude input H/sub d/. The design procedures, theoretical background, results and conclusions are presented in this paper.