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Adaptive and neural control of a wing section using leading- and trailing-edge surfaces

机译:使用前缘和后缘曲面的机翼部分的自适应和神经控制

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This paper treats the question of control of nonlinear aeroelastic responses of a prototypical wing section with structural nonlinearity using leading- and trailing-edge control surfaces. It is assumed that all the aerodynamic, structural and inertia parameters are unknown to the designer. As such the limitation of a recent control design reported in the literature, which requires complete knowledge of aerodynamic derivatives and inertia parameters, is removed. An adaptive controller and a neural control system are designed for the trajectory control of the plunge displacement and pitch angle. For the derivation of the adaptive control law, a linearly parameterized model is used but the neural controller is designed by treating the stiffening-type structural nonlinearity as an unstructured function (not parameterizable). It is shown that the adaptive and neural controllers accomplish trajectory control in the closed-loop system. Simulation results are presented which show that these controllers are effective in regulating the nonlinear responses to the origin in the state space in spite of large model uncertainties. Moreover unlike the model with a single trailing-edge surface, two control surfaces provide flexibility in shaping both the plunge and pitch responses.
机译:本文讨论了使用前缘和后缘控制面控制具有结构非线性的原型机翼截面的非线性气动弹性响应的控制问题。假定设计人员不了解所有空气动力学,结构和惯性参数。这样,消除了文献中报道的需要完全了解空气动力学导数和惯性参数的最新控制设计的局限性。设计了自适应控制器和神经控制系统,用于对柱塞位移和俯仰角进行轨迹控制。为了推导自适应控制律,使用了线性参数化模型,但通过将加劲型结构非线性视为非结构化函数(不可参数化)来设计神经控制器。结果表明,自适应控制器和神经控制器在闭环系统中完成了轨迹控制。仿真结果表明,尽管存在较大的模型不确定性,但这些控制器仍有效地调节了状态空间中对原点的非线性响应。此外,与具有单个后缘表面的模型不同,两个控制表面在调整切入和俯仰响应时都具有灵活性。

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