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Multivariate spline-based adaptive control of high-performance aircraft with aerodynamic uncertainties

机译:空气动力学不确定性的高性能飞机基于多元样条的自适应控制

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摘要

In this paper, a new modular adaptive control system is presented to compensate for aerodynamic uncertainties in high-performance flight control systems. This approach combines nonlinear dynamic inversion with multivariate spline-based adaptive control allocation. A new real-time identification routine for multivariate splines is presented to compensate for aerodynamic uncertainties in the control allocation system. This method, indicated as spline-based adaptive nonlinear dynamic inversion, is applied to control an F-16 aircraft subject to significant aerodynamics uncertainties. Simulation results indicate that the new controller can tune itself each time a model error is detected and has superior adaptability compared to an ordinary polynomial-based adaptive controller. Multivariate splines have sufficient flexibility and approximation power to accurately model nonlinear aerodynamics over the entire flight envelope. As a result, the global model remains intact. Although a part of the model is being reconfigured using incoming observations, the remainder of the model remains unchanged and can be used as an a priori source of information. This prevents the occurrence of sudden fundamental changes in the global model structure, which are experienced when using ordinary polynomials.
机译:在本文中,提出了一种新的模块化自适应控制系统,以补偿高性能飞行控制系统中的空气动力学不确定性。这种方法将非线性动态反演与基于多元样条的自适应控制分配相结合。提出了一种新的用于多元样条的实时识别例程,以补偿控制分配系统中的空气动力学不确定性。这种方法表示为基于样条的自适应非线性动态反演,适用于控制F-16飞机在空气动力学方面存在很大的不确定性。仿真结果表明,与基于普通多项式的自适应控制器相比,每次检测到模型错误时,新控制器都可以进行自我调整,并且具有出色的适应性。多元样条具有足够的灵活性和逼近能力,可以准确地模拟整个飞行包线内的非线性空气动力学。结果,全局模型保持不变。尽管使用传入的观测值对模型的一部分进行了重新配置,但模型的其余部分保持不变,可以用作先验信息源。这样可以防止在使用普通多项式时会在全局模型结构中发生突然的基本变化。

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