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Neural Network controller for two-degree-freedom helicopter control system

机译:二自由度直升机控制系统的神经网络控制器

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Now a day automatic flight control is a crucial issue especially for emergency services. One of the fittest candidates for such services is two-degree-freedom (2DOF) helicopter. Automatic control features of 2-DOF helicopter are usually approximated using the linear quadratic regulator (LQR), which can be further enhanced in-terms of Neural Network (NN). Hence, this paper presents the nonlinear flight control of 2DOF helicopter using NN. A back propagation, feed forward NN model is developer and employed to approximate the nonlinear control features of 2DOF helicopter using Matlab software. The effectiveness of the basic 2DOF helicopter NN controller is apparent (∼ 2% pitch and 14% yaw improvement) compared to the conventional (LQR) methods.
机译:如今,自动飞行控制已成为至关重要的问题,尤其是对于紧急服务。此类服务最合适的候选人之一是两自由度(2DOF)直升机。通常使用线性二次调节器(LQR)来估计2-DOF直升机的自动控制功能,此功能可以在神经网络(NN)的范围内得到进一步增强。因此,本文提出了使用神经网络的2自由度直升机的非线性飞行控制。开发了反向传播,前馈神经网络模型,并使用Matlab软件将其用于近似2DOF直升机的非线性控制特征。与常规(LQR)方法相比,基本2DOF直升机NN控制器的有效性显而易见(螺距约2%,偏航角提高14%)。

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