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

机译:两度自由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:现在,一天的自动飞行控制是一个关键的问题,特别是紧急服务。 这种服务的最适合候选人之一是两级自由(2DOF)直升机。 2-DOF直升机的自动控制特征通常使用线性二次调节器(LQR)来近似,这可以进一步增强神经网络(NN)。 因此,本文介绍了使用NN的2DOF直升机的非线性飞行控制。 反向传播,馈送前向NN模型是开发人员,采用使用MATLAB软件近似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控制器的有效性是显而易见的(&#223c; 2%间距和14%的横摆程度)。

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