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Quadrotor unmanned aerial vehicle controller design and synthesis

机译：四旋翼无人机控制器的设计与综合

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摘要

The field of UAVs is quit rich of applications and it can be considered as one of the major fields that can have great future potential. For the four motors vertical take-off and landing (VTOL) aircraft known as the quadcopter specially. it have drawn great attention of the scientific researchers nowadays. It is considered as a prospective solution to a quit variety of applications. This paper is concerned with modeling and control basics that are of huge concern due to unmanned aerial vehicle model complications, nonlinearity, coupling, inherent instability and parameter values ambiguity. Two types of controllers are designed to reach a stable compensated system around the hovering point. Enhanced PID controller is designed first for the unmanned quadcopter aerial vehicle. Then, Adaptive Neuro Fuzzy Inference controller (ANFIS) is refined for the nonlinear system. Input-output data of the enhanced PID controlled among the entire range of operation are gathered. These informations are used for the ANFIS controller design as learning and checking data. The controller achieved using ANFIS, as a nonlinear controller, are correlated with the enhanced PID controller results achieved at the hovering point of operation. The conclusion from these results affirm the efficiency of the ANFIS as quadcopter nonlinear controller.
机译：无人机领域已经失去了广泛的应用，可以将其视为具有巨大未来潜力的主要领域之一。对于四个马达，垂直起降（VTOL）飞机特别称为四轴飞行器。它引起了当今科学研究者的极大关注。它被认为是许多应用程序的前瞻性解决方案。由于无人飞行器模型的复杂性，非线性，耦合，固有的不稳定性和参数值的含糊不清，本文关注的建模和控制基础备受关注。设计了两种类型的控制器，以在悬停点附近达到稳定的补偿系统。增强型PID控制器是最先为无人​​四轴飞行器设计的。然后，针对非线性系统改进了自适应神经模糊推理控制器（ANFIS）。收集在整个操作范围内受控制的增强型PID的输入输出数据。这些信息用于ANFIS控制器设计，作为学习和检查数据。使用ANFIS作为非线性控制器实现的控制器与在悬停操作点获得的增强PID控制器结果相关。这些结果的结论肯定了ANFIS作为四旋翼非线性控制器的效率。

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