Neural network NARMA-L2 control of a Twin Rotor MIMO System

Senoussaoui Abderrahmene, C. Mohammed, Kacimi Abderrahmane, Hocine Rachida
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引用次数: 1

Abstract

This work presents the design of a nonlinear autoregressive-moving average controller (NARLA-L2) applied to a TWIN ROTOR MIMO SYSTEM (TRMS). This system simulates the dynamic of a helicopter, which is a kind of UAVs; they are the interest of nowadays researches, in particular the control of this system. Because of the difficulty presented in modeling of such non linear systems, a non model control technique is used -to avoid this hard and not exact task-based on neural network structure.So this method is applicable for the control of this type of complex nonlinear system, and its strength is that it is not based on physical modeling that is often far from the real system, thus the ease of synthesizing the corrector with good performances in trajectory tracking and disturbances rejection.
双转子MIMO系统的神经网络NARMA-L2控制
本文提出了一种应用于双转子MIMO系统的非线性自回归移动平均控制器(NARLA-L2)的设计。该系统对无人机中的直升机进行了动态仿真;它们是当今研究的热点,特别是对该系统的控制。针对这类非线性系统建模困难的问题,采用了一种基于神经网络结构的非模型控制技术来避免这种困难和不精确的任务。因此,该方法适用于这类复杂非线性系统的控制,其优点在于它不以物理建模为基础,往往与实际系统相去甚远,因此易于合成具有良好轨迹跟踪和抗扰性能的校正器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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